SPEAKERS

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During the conference you will get insights of renowned speakers who will elaborate on topical issues. The speakers, who have often a long background in the world of inventory, supply chain and reliability will show you how they have dealt with setbacks and risks during their career and how they used this to get the position they have now.

Meet the Speakers

	Adrijit Goswami Professor goswami@maths.iitkgp.ernet.in Department of Mathematics Indian Institute of Technology Kharagpur, India
Dr. Adrijit Goswami is a Professor in the Department of Mathematics, IIT, Kharagpur, India. He has completed his Ph.D. from Jadavpur University in 1992. He has published research papers in several reputed international journals such as IJSS, JORS, EJOR, IEEE, IJPE etc. His skills and expertise lies in Inventory Control, Supply Chain Management, Data Mining, Cryptography and Network Security. He has more than 150 research articles. He is Dean of Continuing Education, Head of Administrative Computer Service Support Centre and; also Chairman of ACSSC/ERP IIS. Title of the talk: A fuzzy rule based deteriorating inventory model under vendor-buyers coordination: A new defuzzification approach of type-2 fuzzy set Abstract: In this paper, a single-vendor and multiple-buyers integrated production inventory model is investigated in which the rate of deterioration of the item changes in accordance with the weather conditions of the particular region. It relies upon the values of certain other parameters or attributes that have a direct influence on the extent of deterioration. These parameter values are easily forecasted and thereby can be utilized to determine the item depletion rate in a certain region which is executed here using the Mamdani fuzzy inference scheme. Besides, a nearest interval approximation formula for the defuzzification purpose of interval type-2 fuzzy numbers (IT2FN) is developed. Its application in the proposed inventory model is brought off by considering imprecise demand patterns at the buyer locations that are known to be in the form of IT2FNs. The model optimizes the total number of shipments to be made to the different buyers within a complete cycle so as to minimize the overall integrated cost incurred. An optimization problem with interval objective function is formulated which is converted to develop a composite goal that defines the interval objective function by reducing it to a single objective problem. A detailed illustration of the theoretical results is further presented with the help of numerical example and to highlight managerial insights, sensitivity analysis is also carried out.
	Asoke Kumar Bhunia Professor akbhunia@math.buruniv.ac.in Department of Mathematics The University of Burdwan Burdwan, West Bengal, India
Dr. Asoke Kumar Bhunia is professor in the Department of Mathematics, The University of Burdwan, India. His research interests include computational optimization, soft computing, interval mathematics, interval ranking, etc. He has published more than 100 research papers in various international SCI journals. He is a reviewer of several Elsevier Science, Springer, Taylor & Francis and other SCI journals. A number of Ph.D. and M.Phil. students have received their degrees under his supervision. He has also written three book chapters, two research monographs and a book entitled 'Advanced Operations Research'. He is an INSA visiting fellow and also an associate editor of the Springer journal 'OPSEARCH'. Title of the talk: Modeling of decision making problems with interval uncertainty Abstract: Due to gradual complexity of day-to-day real life decision making problems, there arises a challenging task to the engineers / system analysts / managers for finding the best decision from those problems. Most of the real life decision-making problems can be modelled as nonlinear constrained/unconstrained optimization problems. Again, due to the complexity as well as the uncertainty of different systems in reality, the corresponding problems are non-linear in nature. Again, in most of the real-life optimization problems, the values of different parameters are imprecise due to uncertainty. This impreciseness of different parameters is represented by several approaches. Among these, interval approach is most significant. Again, if the parameters are interval valued, the objective function and /or constraints of the corresponding optimization problems are interval valued. The goal of this talk is to discuss about the modeling of reliability optimization problems and inventory problems with interval uncertainty.
	Bhavin J. Shah Associate Professor bhavinj@iimidr.ac.in Operations Management and Quantitative Techniques IIM Indore, Indore, India
Dr. Bhavin J. Shah is working as faculty in the area of Operations Management and Quantitative Techniques at IIM Indore. He holds PhD in Statistics and Operations Research from School of Sciences, Department of Statistics at Gujarat University. He is a member (CA) of Institute of Chartered Accountants of India. His current areas of research interest include Supply Chain Modeling; Healthcare Delivery Models; Perishable Inventory Systems; Revenue Sharing Models in coordinated supply chains. He has research experience of about ten years and has been publishing research papers regularly. He has published research papers so far in peer reviewed international and national journals like Asia Pacific Journal of Operations Research (APJOR); OPSEARCH; International Journal of Operations Research (IJOR), International Journal of Mathematics in Operational Research (IJMOR); International Journal of Services in Operations Research (IJSOM); International Journal of Business Performance and Supply Chain Modeling (IJBPSCM); International Journal of Data Analysis Techniques and Strategies (IJDATS) etc. He has been working as a referee for a number of national and international journals. Title of the talk: Inventory Models for Fresh Produces with Display Dependent Demand Abstract: In this talk, various inventory models for fresh produce for retailers will be presented. Freshness condition is a very crucial factor for purchasing decision of fresh produce by the customers and thus impacting the demand. Various forms of capturing freshness will be discussed along-with their complexity in modeling for such inventory systems. Differences in modeling the perishability and freshness aspects will be highlighted. Existing literature has mainly focused on the deterministic demand models in the context of fresh produces. An inventory model will be presented considering product demand based on the stochastic freshness level. The proposed model optimizes retailer's expected profit by determining optimal level of order quantity, shelf space, and price.
	Biswajit Sarkar Associate Professor bsbiswajitsarkar@gmail.com Department of Industrial and Management Engineering Hanyang University, South Korea
Dr. Biswajit Sarkar currently is an Associate Professor in the Department of Industrial and Management Engineering of Hanyang University, South Korea. He has completed his Ph.D. from Jadavpur University. He has published research papers in several reputed international journals. Presently, He is serving as the Editorial Board Member of several journals and recently he became the Editor-in-Chief of the Journal of Engineering and Applied Mathematics, DJ Publications. Title of the talk: A deep-decarbonization and zero carbon strategy in a closed-loop supply chain management Abstract: Emission of zero carbon from any industry is quite impractical way to make zero carbon in any closed-loop supply chain management. An improved strategy to make zero carbon emission is how the industry can transfer the emitted carbon into any other substances. This research is conducted to make a deep-decarbonization procedure for obtaining zero carbon emission within the whole closed-loop supply chain management. Some strategies, like packaging waste,environmental protection laws, legislation rules by the local government, improved quality of products, capturing carbon and its storage, are incorporated within the closed-loop supply chain management. The remanufacturing rate is dependent on quality of products and its quality segmentation. The carbon cap is reduced after a certain period of time, whereas the quality of return products follows a Poisson distribution. The model is formulated with respect to some strategical constraints and solved with analytical techniques to obtain the optimal decision variables. An algorithm is developed to obtain the numerical results and an illustrative example, some graphical representations, sensitivity analysis are given to validate the model numerically. Numerical studies find that after a certain year, the effect of deep-decarbonization comes into play and the industries will be passing through zero carbon emission forever.
	Chandra B. Gupta Professor cbbits@gmail.com Department of Mathematics Birla institute of Technology and Science, Pilani, Rajasthan, India
Dr. Chandra B. Gupta who is presently working as a Professor in the Department of Mathematics and having a very rich experience of more than 30 years in teaching and research, obtained his Master's degree in Mathematical Statistics and Ph.D. in Operations Research from Kurukshetra University, Kurukshetra (India). His field of specialization include Applied Statistics, Optimization and Operations Research, on these topics he has published/ presented more than 75 research articles in peer reviewed national, international journals and national & international conferences. Apart from these Dr. Gupta has been chief editor for the proceedings of first to sixth international conference on Operations Research and Statistics. He is also on the editorial board and reviewer of a number of national and International journals. He was also awarded best paper award at the annual conference of National Academy of Science India in December 2009. He has participated in more than 60 national and International conferences in which he has delivered invited talks and chaired technical sessions and also has organized a number of national conferences, workshops in BITS Pilani and in other institutions as well. Title of the talk: First Birth Interval: Some Recent Evidences from Rajasthan Abstract: First birth interval has always been at the forefront of demographers due to its impact on all demographic and non-demographic characteristics of a female. In present study an attempt has been made to analyse the data from N.F.H.S.-3 for an Indian state Rajasthan. We tried to identify the link between various socio-economic and demographic factors with first birth interval of a female. In addition to statistical measures, proportional hazard analysis in combination with life table was applied to investigate the impact of various factors on first birth interval.
	C. Elango Associate Professor chellaelango@gmail.com Department of Mathematical Sciences Cardamom Planters' Association College, Bodinayakanur, TN, India
Dr. C. Elango is a chairperson in the Research Department of Mathematics, Cardamom Planters' Association College. He received his PhD in Mathematics from the Madurai Kamaraj University, Madurai, Tamilnadu, India, in 2002. His skills and expertise lies in Stochastic Modelling: Inventory and Queues, Markov Decision Processes and Fuzzy Sets and Systems. He has published a good number of research papers in several prestigious peer-reviewed international and national journals. Title of the talk: Optimal Inventory Control in Supply Chain with Retrial Demand - Semi-Markov Decision Process Abstract: Markov Decision Process is a controlled stochastic dynamic programming problem which is used to solve many real world automation and AI problems. Partially observable MDP is the generalized problem of MDP in which the observation before decision making is not complete, only a partial portion is available. In this model we considered a MDP in a Two-Echelon Supply Chain System in which the inventory replenishment is controlled by observing the inventory position and size of the orbit. In this talk, I will describe the fundamental principles of MDP and its applications in inventory and service control in service facility systems. How to use LPP techniques to get optimal ordering /service policy suitable to the given system is our major focus with specific numerical examples.
	Gede Agus Widyadana Senior Lecturer gede@petra.ac.id Faculty of Industrial Technology Petra Christian University, Surabaya, Indonesia
Dr. Gede Agus Widyadana is a senior lecturer in Industrial Engineering Department, Faculty of Industrial Technology, Petra Christian University, Surabaya, Indonesia. He received his Master of Engineering degree from Asian Institute of Technology, Bangkok and his PhD degree in Industrial and Systems Engineering, Chung Yuan Christian University, Taiwan. His research interests are in the field of inventory modelling, optimization, and simulation. He has published papers in refereed journals such as International Journal of Production Economics and OMEGA, international conferences. He also a consultant and speaker for some industries in Indonesia. Title of the talk: Optimal deteriorating inventory models in difference supply life cycle Abstract: Fruits and vegetables are two examples of deteriorating items that decay, damage, spoilage, obsolescence, pilferage, or loss of marginal values of a commodity. Research on deteriorating inventory items is one of the interesting topics and developed intensively for many years. However, most of them considering constant supply availability. In reality, most fruits and vegetable supply are not available constantly through a year. Every fruits and vegetable have their own supply life cycle. In the other side, customer demands are affected by the supply availability or harvest period, therefore different inventory deteriorating models should be developed to solve the unique supply characteristics. This talk will discuss different deteriorating items supply periods and their related optimization models. The models are considering unavailability supply and different demand types. A numerical example is shown for each deteriorating inventory model and some interesting management insights are presented.
	Gokul Chandra Sharma Professor gokulchandra5@gmail.com Department of Mathematics IBS, Khandari, Agra, India
Dr. Gokul Chandra Sharma is Former mathematics professor at Agra University. and having a very rich experience of more than 35 years in teaching and research. His achievement includes research in computational fluid dynamics, operations research and biomathematics, books advance discrete mathematics, numerical analysis, integral transforms, hydrodynamics, rigid dynamics, Research in differential equations, differential geometry, dynamics, statics, hydrostatics, three-dimensional coordinate geometry, real analysis and Research in two-dimensional coordinate geometry, differential calculus, integral calculus, algebra, matrices, vector algebra and calculus, special functions, unified Rekhik Beejganit. He is Member Operations Research Society India (life, president Agra chapter), Indian Society Industrial and Applied Mathematics, Indian Mathematics Society, Indian Science Congress, Global Society Mathematics and Allied Sciences. He has also Recipient prize for best article, Agra University, 1969, Distinguished Services award Vijnana Parishad of India, president VPI. Title of the talk: Maintainability and performance modeling of GIX/GY/R machining system with balking: a diffusion approximation approach Abstract: This paper is concerned with the GIX/GY/R machine repair model having general identically distributed failure and repair processes of machining components with mixed spare provisioning. The balking behavior of the care taker, who is taking responsibility of the maintainability of the system, is considered. The repairmen switch over to faster rate in case queue of failed machines is build up. By using the means and square coefficients of the variation of batch size as well as distributions of the failure and repair times, the diffusion equation is constructed. For the solution purpose, the boundaries are imposed at the origin and other end. The combination of elementary return boundary conditions and discretization is used to obtain the queue size distribution of the number of failed machines in the system. We derive the approximate results for the performance measures using the steady-state distribution for the diffusion process. By taking illustration, numerical simulation is carried out to facilitate the sensitivity analysis.
	Gopalan Srinivasan Professor srini@unb.ca Faculty of Business Administration University of New Brunswick, Canada
Dr. Gopalan Srinivasan joined the Faculty of Business Administration University of New Brunswick in 1987. His research has included supply chain management/inventory theory, working capital management, accounting policies, corporate finance, investments, international business and human development index. He has over 100 journal articles and refereed proceedings. Prior to joining the Faculty, Dr. Srinivasan was an Associate Professor at the Indian Institute of Management, Ahmedabad, India. Dr. Srinivasan was an Area Editor for the International Journal of Production in Quantitative Methods and was a member of the Editorial Review Board for Decision Sciences. Title of the talk: Research Journey: A Process Story Abstract: In this presentation drawing from personal experience. I address key processes involved in research. The insights drawn from my long-term collaborator late Dr. Francisco J. Arcelus and my work with several others is presented in a way to be useful for researchers. Lessons learned from both success and not so success stories will be the focus of the presentation.
	Hui Ming Wee Professor weehm@cycu.edu.tw Department of Industrial and Systems Engineering (ISE) Chung Yuan Christian University, Taiwan
Dr. Hui M. Wee is an Associate Dean and distinguished Professor at the Chung Yuan University, Taipei. He is an expert of inventory management. He has more than 274 research articles with around 9,341 reads and 5,442 citations. Title of the talk: Sustainable supply chains under carbon cap scheme Abstract: Nowadays, environmental concern has become an outcry for green movement. Hence, minimizing the amount of emissions is as important as minimizing the total cost of the supply chain. This study is motivated by the facts that most third party logistics (3PLs) ignore the urgencies of green logistics and prefer to focus only on minimizing costs. Other motivation includes the increasing global warming and the possibility of energy scarcity for the next decades. We present two scenarios: original policy and carbon cap scenario. The performance of the proposed model for each scenario is evaluated and compared. Our aim is to develop a strategic balance between economic aspect (low cost) and environmental requirement (less pollution). We take a fresh look at the impact of logistics and stricter legislations on environment. The trade-off between transportation cost and carbon emission in freight consolidation and containerization problem is discussed using a real-world business case study.
	K. V. Subbaraya Sarma Professor smskvs@gmail.com Department of Statistics Sri Venkateswara University, Tirupati, India
Dr. K. V. Subbaraya Sarma is Rtd. Professor from Department of Statistics, Sri Venkateswara University, Tirupati, India. His teaching Experience is more than 40 years and expertise lies in Inventory Control, Quality Control, ROC Curves, Statistics. He has published more than 70 research papers in various national/international journals such as EJOR, IJCSC, IJMS, IJSM, IEJ, IJPE, OPSEARCH etc. He has authored several books on Statistics. He is also consultant in Data Analysis. Title of the talk: Inventory Modeling - the perceptions of the teacher, the researcher and the practitioner Abstract: Inventory modeling is an interesting area of Operations Research taught at various levels of graduation and above. The well-known Wilson's EOQ formula gave impetus to researchers resulting in improvements on the basic model with realistic assumption. Several inventory models are taught to the students of engineering, science and management as a part of the curriculum. Researchers across the globe formulated new models incorporating aspects like product deterioration, multiple items, multiple locations, stock dependent demand, deferred payments etc. Stochastic inventory models with realistic assumptions on demand and supply processes formed another cluster of models studied by researchers and known to have interesting applications like rail and air ticket reservation, hospital inventory management etc. The practitioner however prefers to adopt the results of research only through simple working rules or with a software application. In this talk we appraise the status of teaching and research in the field of inventory management and touch upon the statistical and data science methods for efficient implementation of the models. More engineering is needed to transform the gist of the current research into user-friendly software tools.
	Kripasindhu Chaudhuri Former Professor & Emeritus Fellow (UGC & AICTE) chaudhuriks@gmail.com Department of Mathematics, Jadavpur University Kolkata, West Bengal, India
Dr. Kripasindhu Chaudhuri, Professor of Mathematics in the Department of Mathematics Jadavpur University, Calcutta, West Bengal, India. Dr. Chaudhari having a very rich experience of around 50 years in teaching and research, obtained his Master's and Ph. D. degree in Mathematics. His field of specialization Operations Research, Mathematical Ecology, History of Mathematics, Fluid Dynamics on these topics he has published/ presented more than 250 research articles in peer reviewed national, international journals. He has participated in more than 125 national and International conferences in which he has delivered invited talks and chaired technical sessions. Apart from these Dr. Chaudhari has been fellow of F. N. A. Sc. (Fellow of the National Academy of Sciences), India, 1996; and F. I. M. A. (Fellow of the Institute of Mathematics and its Applications), United Kingdom, 1999. He has visited Budapest University, Hungary, as a Fellow under the Indo-Hungarian Cultural Exchange Programme, 1983; ICTP (International Centre for Theoretical Physics), Trieste, Italy, as a Fellow under Visiting Mathematicians' Programme, 1986; NCSU (North Carolina State University), Raleigh, USA, as a FULBRIGT FELLOW, 1989; and worked as visiting Professor at Thammasat University, Bangkok, Thailand, 2002. He is also on the editorial board and reviewer of a number of national and International journals. Title of the talk: Two-echelon manufacturer-retailer supply chain strategies with price, quality and promotional effort sensitive demand Abstract: This study deals with the two-layer supply chain model of one manufacturer and one retailer for a single product where market demand is assumed to be dependent on selling price, quality of the product and promotional effort of the retailer. The behaviour of the supply chain under centralized, manufacturer Stackelberg, conditional manufacturer Stackelberg, retailer Stackelberg, conditional retailer Stackelberg and vertical Nash model structure is investigated. The nature of the above models provides great insights to a firm's manager for achieving optimal strategy in a competitive marketing system. Quite often, not all items produced in a firm are of perfect (conforming) quality and others are of imperfect (nonconforming) quality. The nonconforming products are sold in secondary shops or by other retailers. The procurement cost of finished products depends on the quality of the products due to more investment in advanced technology, better raw materials, skilled labours, etc. The warranty policy for the products is also imposed to attract the customers to buy more. Here both the members (manufacturer and retailer) jointly share the cost of the warranty policy. The objective of this paper is to determine the optimal selling price and promotional effort of the retailer, while the optimal wholesale price and quality of the products are determined by the manufacturer so that the above strategies are maximized. Finally, the numerical examples with sensitivity of the key parameters are illustrated to investigate the proposed models.
	Kusum Deep Professor kusumfma@iitr.ac.in Department of Mathematics Indian Institute of Technology Roorkee Roorkee, Uttarakhand, India
Dr. Kusum Deep is a Professor in Department of Mathematics, IIT Roorkee. She has completed her Ph.D. in Mathematics from University of Roorkee. She has over 100 articles in journals, 78 articles in Conference proceeding and 9 chapters in books. Her major areas of interest are Numerical Optimization, Nature Inspired Optimization, Computational Intelligence, Genetic Algorithms, Particle Swarm Optimization Parallel Computing, Parallel Genetic Algorithms and Parallel Particle Swarm Optimization. She is a member of IEEE and president of Soft Computing Research and Executive Editor of International Journal of Swarm Intelligence, Inderscience. She is also secretary of Forum of Interdisciplinary Mathematics and life member of Indian Science Congress. Title of the talk: Grey Wolf Optimization and its Applications Abstract: Often it is desired to determine a global optimal solution rather than a local optimal solution of a nonlinear optimization problem. In comparison to conventional computing paradigms, nature inspired optimization techniques are helpful to solve real world optimization problems. Apart from Genetic Algorithms and Particle Swarm Optimization, one of the most popular techniques is the Grey Wolf Optimization (GWO) proposed by Mirjalili et al in 2014. This interesting technique is based on the leadership hierarchy behaviour of the randomly generated solutions in the search space. The population is called a pack. The objective of the pack is to encircle and kill the prey. For doing this, the best grey wolf (solution having best objective function values) is called alpha (α), whereas the second and third best solutions are called beta (β) and delta (δ), respectively. The remaining solutions are called omega (ω). Each wolf in the pack randomly updates its position during each iteration based upon the current position of the prey. Many researchers have proposed improved versions of GWO and performed theoretical studies on the effects of various parameters of the algorithm. Also, GWO has been applied to many real life applications. This talk will focus on this interesting algorithm. Firstly the fundamentals and principles of the algorithm will be presented, then a step-by-step numerical example will be used to illustrate the working of the algorithm. The talk will also explain some of the improved variants that have been developed at my research group at IIT Roorkee. The talk will end by illustrating the use of the GWO on some real life applications.
	Leopoldo Eduardo Cárdenas-Barrón Professor lecarden@tec.mx School of Engineering and Sciences Tecnológico de Monterrey, Monterrey, Mexico
Dr. Leopoldo Eduardo Cárdenas-Barrón is currently a Professor at School of Engineering and Sciences at Tecnologico de Monterrey, Campus Monterrey, Mexico. He is also a faculty member in the Department of Industrial and Systems Engineering at Tecnologico de Monterrey. He was the associate director of the Industrial and Systems Engineering programme from 1999 to 2005. Moreover, he was also the associate director of the Department of Industrial and Systems Engineering from 2005 to 2009. His research areas include primarily related to inventory planning and control, logistics, supply chain and optimization. He has published papers and technical notes in several journals. Title of the talk: A general approach to obtain near optimal solution for mixed integer programming problems by obtaining a reduced set of decision variables: The cases of inventory lot sizing with supplier selection problem, and selective and periodic inventory routing problem Abstract: This work proposes a simple and general approach to solve mixed integer programming (MIP) problems. The approach is based on creating a reduced set of decision variables and then optimizing the MIP problem. It is worth to remark that this approach always solves the optimization problem in a small feasible region that contains a near optimal solution; if the reduced set of decision variables contains the optimal solution active decision variables the approach will obtain the optimal solution with less computational effort. This approach is applied to solve two different problems. The first one is related to the multi-product multi-period inventory lot sizing with supplier selection problem. The second one is about selective and periodic inventory routing problem for the wasted vegetable oil collection. Numerical experimentation confirms the success of the approach solving different MIP problems. On the set of the benchmark instances, the approach always found better solutions compared with those previously published. Additionally, it is shown that the approach is effective and efficient in solving very large instances.
	M. Kuber Singh Lecturer moirang1@yahoo.com Department of Mathematics, D.M. College of Science Imphal, India
Dr. M. Kuber Singh is Professor in the Department of Mathematics, D.M. College of Science Imphal, India. He has completed his Ph.D. in Mathematics and M.Sc. in mathematics. His areas of research are Operations Research, Algebraic Coding Theory. He has research experience of about ten years and has been publishing research papers regularly. He has published research papers so far in peer reviewed international and national. He has been working as a referee for a number of national and international journals. He has attended and presented research papers at several national and international conferences in India and abroad. He has also been invited as resource person at various conferences, workshops, seminars. Title of the talk: An Application of Fuzzy Set Theory for Leakage Inventory Models Abstract: The fuzzy set theory has been applied in many fields such as Inventory control theory and management sciences etc. The fuzzy numbers and fuzzy values are widely used in many applications because of their suitability for representing uncertain information. This paper explores what Fuzzy set theory is and how fuzzy numbers can be used in Inventory control theory. A model for solving an inventory control problem in which input data are described by triangular fuzzy numbers will be presented here. It serves to encourage researchers focusing on emerging trends in the study of inventory models in fuzzy environment.
	Manharlal N. Patel Professor mnpatel.stat@gmail.com Department of Statistics Gujarat University, Ahmedabad, Gujarat, India
Dr. Manharlal Patel is a Professor of Statistics in the Department of Statistics, Gujarat University, Ahmedabad. He has completed his PhD from Gujarat University in 1992. He is having a vibrant experience of more than 35 years in teaching and research. His skills and expertise lie in Statistical Inference, Econometrics, Distribution Theory, Data Analysis, Visual Basic Programming. He has published a good number of research papers in several national and international journals and also attended more than 50 conferences and invited talks. He worked as a foreign member in Peer Review Team, nominated by UGC Nepal during 8-12, May 2018 and also a lifetime member in various statistical associations. He is Ex. I/C Director, K. S. School of Business Management, Gujarat University, Ahmedabad (During 2015 to 2017). Title of the talk: A Bayesian approach to optimal warranty length of Weibull life time distributed product Abstract: The profit of a company is directly related to the quality of the manufactured product. The manufacturers attract consumers by providing reliable product. Consumers always think about the warranty of the product which is related to the quality of the product. Warranty is a manufacturer's assurance to a buyer regarding the product. In this talk optimal warranty length of the product having Weibull life time distribution is determined under a Bayesian set up. The information of the product reliability is obtained though the censored sample. The concept of expected utility unction and the information about the product are used to determine the optimal warranty length. The warranty length is determined in case of free replacement warranty (FRW), Pro-rata warranty (PRW) and combined FRW/PRW warranty. For illustration a real data set is used.
	Neelamegam Anbazhagan Professor and Head anbazhagan_n@yahoo.co.in Department of Mathematics Alagappa University, Karaikudi, Tamil Nadu, India
Dr. N. Anbazhagan is currently working as an Head of the Department in the Department of Mathematics, Alagappa University, India. His research interests include Stochastic Inventory Modelling and Data Mining. He has been awarded with distinguished awards including Research Award (2015-17), Shri P. K. Das Memorial Best Faculty Award, Career Award for Young Teachers (2005). He is serving as an editorial member and reviewer of several international reputed journals. He is the member of many international affiliations. He has successfully completed his Administrative responsibilities. He has authored more than fifty research articles/books related to his research interest. Title of the talk: A Queueing-Inventory System with Retrial Customers Abstract: We consider a queueing-inventory system with two types of customers, say, high priority and low priority, arrive according to Poisson processes. The inventory is replenished according to an (s, Q) policy and the replenishing times are assumed to be exponentially distributed. The server provides two types of services - first with ordinary service (essential service) and the second with optional service. The idle server first gives ordinary service to the arriving customers (type 1/type 2). Upon first essential service completion, then the server gives additional service (second optional) only to the type 1 customers. We assume that the type 1 customers have both types of priorities (non-preemptive priority and preemptive priority) over the type 2 customers. We discussed retrial concept only for type-2 customers. The stationary probability distribution of the inventory level, status of the server, number of customer in the orbit and number of customers in the waiting line are obtained by matrix methods and some numerical illustrations are provided.
	Nita H. Shah Professor & Head nitahshah@gmail.com Department of Mathematics Gujarat University, Gujarat, India
Dr. Nita Hasmukh Shah is professor in the Department of Mathematics at Gujarat University Ahmedabad. She has completed her PhD in Mathematics. She has published more than 200 research papers in several reputed National and International journals. Her field of specialization is Mathematics and Operation Research. Her skills and expertise lie in Finance, Modeling and Simulation, Optimization, Operations Management, Logistics, Automation and Robotics, Production Engineering, Production planning, Quality Management, SCM, TQM, DOE, Modelling of infectious diseases etc. Title of the talk: Various Contracts in Furniture's Supply Chain under Price and Sales Effort Sensitive Demand Abstract: This paper analyzes the optimal price and sales effort in supply chain of readymade furniture. Two contracts viz. revenue-sharing contract and wholesale price contracts are considered when demand varies negatively with selling price and positively with sales effort level. The objective is to maximize profits of players and supply chain with respect to effort investment and selling price which can be undertaken either by the retailer or the manufacturer. It is observed that under the wholesale price contract, the retailer is advised to optimize the effort investment level. However, if manufacturer decides effort level, revenue-sharing contract is beneficial to both the players if they jointly decide on consignment.
	P. K. Kapur Professor & Director pkkapur1@gmail.com Amity Center for Interdisciplinary Research Amity University, Noida, India
Dr. P.K. Kapur is Professor & Director Amity Center for Interdisciplinary Research. He served as Professor at Amity International Business School since September 2011 till September 2015. He has Professor and Head in the Department of Operational Research and Dean Faculty of Mathematical Sciences, University of Delhi. He has President, Operational Research Society of India (for 2005 and 2006). His Areas of Specialization is Hardware and Software Reliability, Operations Management, Optimization, Queueing theory, Innovation Diffusion Modelling, Numerical computation of stochastic models and Marketing, Neural Networks, Multi Criteria Decision Making (MCDM), Vulnerability Discovery Modelling, Patching. He is member of International Journal of Performability Engineering Editorial Board and member of International Journal of Decision Support Systems (IJDSS) Editorial Board and life member ORSI. Title of the talk: Optimal decisions on when to release software and stop the testing process using multi-attribute utility theory Abstract: This paper suggests an optimal release time and testing stop time strategy for software products that supports the debugging process to persist for an added period after the software is distributed. The remaining faults in the field are removed by the combined efforts of the testing team and customer's feedback or report. In this study, a new procedure is developed to model the software reliability growth process, which is based on the assumption that the tester's bug-detection rate modifies after the product release. In software engineering, the time instance at which bug detection rate alters is known as change-point. Moreover, the unified approach is employed to model the generalized framework for bug detection phenomenon. A utility-based optimization problem is developed to optimize the software time-to-market and testing termination time by using the multiple attributes. Consequently, a multi-criteria decision-making (MCDM) technique known as multi-attribute utility theory (MAUT) is applied to evaluate the decision variables. The results of the proposed optimal release policy known as the release policy with field-testing (FT) is compared with the conventional release time policy, i.e., the release policy with no field-testing (NFT). The parameter estimation is performed on the actual fault observation data. Besides, the applicability of the optimization problem is interpreted using a numerical illustration, encompassing both exponential and logistic bug-detection process.
	Prakash Abad Professor abad@mcmaster.ca DeGroote School of Business McMaster University, Canada
Dr. Prakash Abad, Professor of Operations Management at DeGroote School of Business, McMaster University, Canada. He has completed his Ph.D. in Management Science from University of Cincinnati. Dr. Abad research interests include inventory management, statistical data analysis, and non-linear and stochastic optimization. He teaches courses in operations research/management science, logistics, production/operations management and statistics both at the graduate and undergraduate level. Professor Abad's research has appeared in Management Science, Decision Sciences, European Journal of Operations Research, Optimal Control and Applications, International Journal of Systems Science, Computers and Operations Research, Journal of the Operational Research Society, and IIE Transactions. He has consulted on issues involved in repeat buying theory. He is a member of Institute for Operations Research and the Management Sciences (INFORMS), American Institute for Decision Sciences, Canadian Operational Research Society (OCRS), and Production and Operations Management Society (POMS). Title of the talk: A two stage extension of the price setting newsvendor problem Abstract: We present a two-stage pricing and inventory model for a seasonal product assuming the multiplicative error demand function. We assume that the reseller can place only one order for the season whereas he can revise the selling price for the good mid-season. We model total demand in each sub-interval assuming that the expected total demand is a decreasing function of the selling price and the error term in the demand function is multiplicative. Assuming that the objective is to maximize expected profit, we develop a two-stage stochastic optimization procedure to determine the order size, the period-one price and and an algebraic rule for setting the period-two price.
	R. Uthayakumar Professor & Head uthayagri@gmail.com Department of Mathematics The Gandhigram Rural Institute Gandhigram, Tamil Nadu, India.
Dr. R. Uthayakumar is presently working as Professor and Head in the Department of Mathematics, The Gandhigram Rural Institute Gandhigram, Tamil Nadu, India and having a very rich experience of more than 24 years in teaching and research. He has more than one fifty research papers in area of Operations Research, Inventory Management and Control. His publications appeared in prestigious peer reviewed international and national journals. Apart from this, he has completed industrial projects sponsored by UGC, CSIR, NHBM, DST-SERB etc. Title of the talk: A comparison between non-coordination and coordination under trade credit policy in stochastic demand Abstract: A two-echelon supply chain with one manufacturer and one retailer is developed for multi products is developed. The retailer faced with the uncertain demand for all products which follows a normal distribution. The production process is assumed to be imperfect, and the defectiveness is assumed to follow a beta distribution. The manufacturer produces and delivers the products in a number of equal sized batches to the manufacturer's warehouse, and thereby it is delivered in a number of equal batches to the retailer's warehouse. Shortages are allowed to occur, at the retailer side, and it is backordered partially. The retailer offers a price discount for backordered items to his customers. Both the lead time crashing cost and the partial backorder ratio are considered as the inverse function of lead time. Under these assumptions, there are three inventory models proposed, one with non-integrated approach, the other with an integrated approach without trade credit and finally an integrated approach with trade credit. A new iterative algorithmic procedure has been developed to minimize the total cost. Finally, numerical examples are given to illustrate the models and the sensitivity analysis is conducted over various model parameters.
	Ramakrishnan Ramanathan Professor & Director ram.ramanathan@beds.ac.uk Business and Management Research Institute University of Bedfordshire, Bedfordshire, UK.
Dr. Ramakrishnan Ramanathan is a Professor of Operations Management and Director in the Business and Management Research Institute (BMRI). He has completed his Ph.D. in Industrial Management from Indian Institute of Technology. He has over 130 research articles 5 books/Monographs and over 160 conference/invited/tutorial presentation to his credit. His interests lie in management science tools of linear programming, goal programming, data envelopment analysis, statistical tools and the analytic hierarchy process. He is an area editor in the field of Multi-Criteria Decision Making for the journal 'OPSEARCH', the journal of the Operational Research Society of India. Title of the talk: The value of Business Analytics in Supply chains and Logistics Abstract: The invited talk will review the use of Business Analytics in supply chains and logistics, and then present results of a qualitative study in the UK aimed at understanding contemporary practice of using Business Analytics in improving performance of SCM and logistics companies by conducting exploratory case studies. Based on an in-depth analysis, a value-adding-input-output framework is presented to support understanding of the use of Business Analytics in logistics companies.
	Samarjit Kar Associate Professor and Head dr.samarjitkar@gmail.com Department of Mathematics National Institute of Technology, Durgapur, India
Dr. Samarjit Kar, Associate Professor and Head, Department of Mathematics, National Institute of Technology, Durgapur, India. His current research interests include operations research and optimization, soft computing, uncertainty theory and financial modelling. He has published over 90 referred articles in international journals. His publications appeared in prestigious journals including European Journal of Operational Research, Computers and Operations Research, Annals of Operations Research, International Journal of Production Economics, IEEE transactions on Fuzzy Systems, Information Sciences, Expert Systems with Applications, Applied Soft Computing, Applied Mathematical Modelling, Computers and Industrial Engineering, Applied Mathematics and Computation. He is serving as Associate editors of IEEE Transaction on Fuzzy Systems and Journal of Uncertainty Theory and Applications (Springer). Title of the talk: Advances in Evolutionary Algorithms and Applications to Combinatorial Optimization Problems Abstract: In the real world logistics and supply chain management there are many combinatorial optimization problems (COP) imposing on more complex issues, such as complex structure, nonlinear constraints, and multiple objectives to be handled simultaneously and make the problem intractable to the traditional approaches because of NP-hard nature COP. For developing an efficient algorithm whose computational time is small, or at least reasonable for NP-hard combinatorial problems met in practice, we have to consider the following very important issues: - quality of solution, - computational time, and - effectiveness of the nondominated solutions for multiobjective optimization problem (MOP). Evolutionary algorithm (EA) is a subset of metaheuristics, a generic population-based metaheuristic such as genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). EA is based on principles from evolution theory, and it is very powerful, and broadly applicable stochastic search and optimization technique which is effective for solving various NP hard COP models. This invited lecture will be firstly introduced a brief survey of several metaheuristics based on EA such as GA, hybrid GA (HGA), multiobjective GA (MoGA), PSO and multiobjective PSO for applying to various combinatorial optimization problems. Secondly real applications based on multiobjective metaheuristics will summarize the following topics: 1. Logistics and transportation management, 2. Supply chain management
	Sarla Pareek Professor & Dean psarla13@gmail.com Department of Mathematics & Statistics Banasthali Vidyapith, Rajasthan, India
Dr. Sarla Pareek, Professor & Dean, Department of Mathematics & Statistics, Banasthali Vidyapith. She has completed his Ph.D. from Banasthali Vidyapith. She has published research papers in several reputed International journals. She is an expert of Applied Statistics, Time Series Analysis in demography, Inventory Theory. Title of the talk: Inventory Accuracy with Statistical Process Control-An Insight Abstract: Inventory accuracy is a critical and highly sensitive area which affects the firms. It deals with checking and maintaining the records to ensure the right quantity, of the right item, in the right location, at the right time. When inventory is located correctly and warehouse pickers do not have to search for items, productivity will increase. Customer service will also increase due to more accurate stock information, less backordering, and fewer stock-outs. Some commonly used methods for inventory accuracy are physical inventory process and cycle counting. Distributers who use physical inventory process verify their stock keeping units once a year. Many companies use the technique of cycle counting for improving inventory accuracy. Cycle counting is intended to comprehensively examine all the stock keeping units over the time through sequential and collective counting exercise. SPC is a demonstrated factual strategy used in screening process to enhance quality using variance reduction. SPC utilizes random samples to monitor and control a process to ensure it. An advantage of SPC is that it requires reduced resource expenses because it uses sampling techniques not a 100 percent inspection. Nowadays SPC has been established as an efficient method of inventory accuracy. Thus, an attempt has been made to apply statistical process control (SPC) for monitoring inventory accuracy.
	Shib Sankar Sana Professor shib_sankar@yahoo.com Department of Mathematics Bhangar Mahavidyalaya, Bhangar, West Bengal, India
Dr. Shib Sankar Sana is a Professor in the Department of Mathematics, Bhangar Mahavidyalaya, India. He has completed his Ph.D. from Jadavpur University. He is skills and expertise lie in Inventory, Production Planning and Control, Bio-mathematics and Supply chain management. He has published research papers in several reputed international journals. Title of the talk: A mathematical model on eco-friendly manufacturing system under probabilistic demand Abstract: The article deals with a mathematical model of production inventory system of green products in a green manufacturing industry. The main objective of this proposed model is to formulate a profit function for service level and random variable dependent demand implementing green technology in the manufacturing industry where green house gas emissions are reduced. The production lotsize is considered here as an increasing function of green technology and capital invested for setup the manufacturing system that meets the market demand. As a result, green technology, capital invested for setup and service level are decision variable which are optimized to achieve maximum profit. Finally, numerical example for normal distribution and distribution free case are illustrated to justify the proposed model.
	Snigdha Banerjee Professor bans_1@rediffmail.com School of Statistics Devi Ahilya University, Indore, India
Dr. Snigdha Banerjee is professor in the School of Statistics, Devi Ahilya Vishwavidyalaya, Indore, India. She has published papers in the field of Operations Research, bioinformatics, design of experiments and management. She has worked on various projects of applications of Statistics and Operations Research methods in the field of economics, management, computers, engineering, biological models etc. A number of Ph.D. and M.Phil. Students have received their degrees under her supervision. Title of the talk: Buyer's Optional Partial Advance Payment Policy for Stochastic Inventory Model with Price and Time Dependent Demand under Trade-Credit Abstract: In a supply chain, although the availability of credit period enables multiple advantages for the buyer, it has a negative impact on the supplier's cash flow, as the supplier does not receive cash from his sales immediately. In the current business scenario where many of the dominating manufacturers are demanding considerably longer credit periods from their suppliers, this negative impact is further amplified. A remedial action is proposed in terms of the supplier asking the buyer to make an optional partial advance payment with the discount being reasonably decided upon by the buyer. For a single product having stochastic price and time dependent demand in a single buyer single supplier supply chain, we investigate the buyer's payment and ordering decisions when discount is available for the optional advance payment, where the supplier sets his selling price, period of optional advance payment and the credit period.
	Suraj Rane Professor ssr@gec.ac.in Mechanical Engineering Department Goa College of Engineering, Farmagudi, Ponda, Goa, India
Dr. Suraj Rane is a Professor in the Department of Mechanical Engineering at Goa College of Engineering, Farmagudi, Goa and has a total of 20 years of teaching experience and 1 year of industrial experience. He has completed his BE (Mechanical Engineering) and ME (Industrial Engineering) from Goa University. He holds PhD in Reliability Engineering from Indian Institute of Technology (IIT) Bombay. His current areas of research interest are Quality Engineering, Reliability Engineering, Maintenance Engineering, Six Sigma and Optimization. He is the current Chairman of Indian Institution of Industrial Engineering (IIIE) - Goa Chapter. He was the Chairman Board of Studies in BE (Mechanical Engineering) and ME (Industrial Engineering) of Goa University. He is the member of various professional bodies like Quality Council of India, ISTE, ORSI, SAE-INDIA, IAPQR, SREQOM, SRESA and IISA. He is on the reviewer panel of international journals in the areas of Quality, Reliability and Maintenance Engineering. Title of the talk: Design for Robustness and Reliability: Approach and application Abstract: Variation in product's critical-to-quality characteristic over a period of time affects its performance forcing the customer to shift brand loyalty. Various strategies are available aiming for variation reduction. One of them is Taguchi methods, which is also called as Robust Design (RD) methods. Optimal levels of significant variables are found using this approach which will ensure minimum effect on the response, thus making the product robust. Simultaneously, the other crucial area to concentrate is ensuring high reliability. The practical approach discussed in this work is called Design for Robustness and Reliability (DFRR), which focuses on reducing variation and improving reliability. DFRR combines strength of Robust Design (RD) methodology and Design for Reliability (DFR). This approach is illustrated to understand its benefits, challenges and limitations with an application in industry.
	Suresh C. Malik Professor sc_malik@rediffmail.com Department of Statistics M. D. University, Rohtak, Haryana, India
Dr. Suresh C. Malik is presently working as Professor in the Department of Statistics, M.D. University, Rohtak, Haryana. and having a very rich experience of more than 27 years in teaching and research He has authored more than one fifty research articles/books related to his research interest. Apart from authoring a number of books he has presented the papers/talks in India and abroad including the USA, the UK, Portugal, Singapore, Germany, France, Belgium and Switzerland. He is the founder President of Indian Association for Reliability and Statistics (IARS). He has recently elected as member of the section of Mathematical Sciences of ISCA. Title of the talk: Reliability Measures of a Non Series-Parallel System of five Components with Weibull Failure Laws Abstract: Over the years, a lot of efforts have been made by the manufacturers to develop reliable systems with best possible structures of the components. The existing literature on reliability indicates that system performance can be improved by using either components of good quality or by adopting proper repair policies. The structural design of the components has also been given a considerable importance in order to improve the reliability of the systems. The existing studies also reveal that a system having series-parallel structure of the components is more reliable to use. However, in practice, the systems are not always simple series or parallel. A complex system, on simplification, can produce a non series-parallel structure. Several methods have been used to evaluate reliability of non series-parallel systems. The reliability of a non series-parallel system of five components is computed by providing different flow of information through a single component. The logic diagram technique is used to develop simple parallel paths (called duplication paths) between IN and OUT terminals according to the flow of information. Each path contains components whose successful operation can lead to the success of the system. The paths which dominate over the other paths in the logic diagram are ignored as these paths have no effect on reliability of the system. The failure rates of the components follow Weibull distribution. The expressions for reliability and mean time to system failure (MTSF) are derived to highlight the effect of operating time, failure rate and shape parameter for their arbitrary values on these measures. The results are shown numerically and graphically to highlight more clearly the effect of different parameters on reliability measures.
	Susheel Suri Product Development Head susheel.suri@ambeygroup.in Ambey Laboratories Ambey Group, Gurgaon, India
Dr. Susheel Suri is currently working as Product Development Head in Ambey Laboratories. He has completed his PhD in Organic Chemistry. He has 3 International patents and 12 Indian patents. He has published good number of research papers in several reputed National and International journals. His skills and expertise lie in Pharmaceuticals, Cosmetics, and FMCG Products - More than 30 new products launched in South Asian Countries. He has worked with and in association with Reckitt Benckiser, Hindustan Unilever, Procter & Gamble and Godrej. Also worked in medium level companies like Ayur Cosmetics, Jiva Ayurveda, BBF, Avees Biocos, Nepal Detergents and Ambey Laboratories. Also worked in Reckitt France as Visiting Scientist. Title of the talk: Inventory management, 21st century. A case study - Hero Management vs Zero management Abstract: Inventory Management in nut shell is "Making lots of profit with spending least amount of money and engaging least amount of space". The ground rules are ethics, following the rules of the land and keeping internal as well as external customers happy and satisfied. Presentation has been classified between Zero management, okay type management and Hero management. These sand witch approaches will clearly high light between dos and don'ts. There can be different yard sticks for different type of industries. Benchmark industries like Amazon, Flipkart, and Dell etc. have different modus opperendi than what FMCG giants like Levers, P&G and Reckitt operate with. On the contrary there are a few small scale/disorganized industries which follow the policy of penny wise and pound foolish. They eventually end up running onto losses rather than to make profits. The presenter would like to share his personal experiences in closely working with and monitoring the above type of industries in FMCG sector.
	V. S. S. Yadavalli Professor and Head sarma.yadavalli@up.ac.za Department of Industrial & Systems Engineering University of Pretoria, Pretoria, South Africa
Dr. V. S. Sarma Yadavalli, Professor and Head of Department of Industrial & Systems Engineering, University of Pretoria. He received his Ph.D from Indian Institute of Technology, Chennai in 1983. Professor Yadavalli has published over 150 research paper in reliability queuing, inventory etc. in various international journals. He is an NRF rated scientist and serving in the editorial board of various international journals. Title of the talk: A Single Product Stochastic Inventory System Modulated by A Queueing System and a Compulsory Waiting Period for Re-Ordering Abstract: A continuous review of single product stochastic inventory system is considered in which an adjustable reorder can be placed only after the expiry of a compulsory waiting period (CWP) even if the inventory position of the system demands an earlier placement of are order. Compulsory waiting period follows an exponential distribution with mean 1/(γ). The maximum capacity of the inventory is M. It is assumed that replenishment is instantaneous. Customers arrive to the inventory system according to a Poisson process with rate lembda. There is a single server attached with the inventory and the job of the server is to serve each customer one at a time with one item from the inventory according to first-come-first-out (FIFO) policy. The server takes a random time to serve each customer and this service time follows an exponential distribution with mean 1/(μ). When the server is serving a customer, all other customers queue-up in a waiting room to meet out the FIFO policy. The capacity of the waiting room is assumed to be infinite. When the inventory level is zero, all customers in the queueing system are washed out. The steady-state joint probability distribution for the number of customers in the queueing system and the number of items in inventory is explicitly found. Performance measures such as stationary mean number of replenishment, mean number of demand satisfied and mean number of demand lost are explicitly found. A numerical illustration is provided to highlight the behavior of performance measures of the model.

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