Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, March 8-10, 2016

Reliable capacitated facility location problem: SAA based approach

Megha Sharma and Sumanta Basu Operations Management Area

Indian Institute of Management Calcutta Joka, Kolkata 700104, India

arnaba10@email.iimcal.ac.in, sumanta@iimcal.ac.in

Partha Sarathi Ghosh Cognizant Technology Solution

Kolkata 743502, India parthaghosh.wb@gmail.com

Abstract

Capacitated facility location problem involves choosing a set of locations from a given set of potential locations for establishing facilities, where each potential location has a capacity constraint and fixed cost of establishing the facility. The locations are so chosen that they satisfy the demands of the demand points in a way that minimizes the total cost of establishing the facilities and of transporting goods from facilities to demand points. This conventional facility location problem assumes that once the facilities are established, they are always functional and hence can always meet the demand. In real life this assumption does not always hold. To model this reality, with each potential location we associate a probability representing its chances of being functional. We model this problem as a two-stage stochastic programming problem with recourse. We use sample average approximation method to solve this stochastic integer linear program. Our solution method uses branch and cut method to solve the first stage integer program, and uses Bender’s decomposition method to solve the second stage problems associated with sample points. Keywords Reliable Facility Location Problem (RFLP), Sample Average Approximation (SAA), Stochastic Combinatorial Optimization Biography Megha Sharma is an Assistant Professor in the Operations Management Group at the Indian Institute of Management Calcutta. She is a fellow of the Indian Institute of Management Ahmedabad, and holds a Bachelor of Technology from Malaviya National Institute of Technology, Jaipur in Civil Engineering. She teaches courses on Mathematics, Operations Research, Risk Management, Operations Research in Marketing, Statistics for Business Analytics, Supply Chain Analytics in the post-graduate programmes and executive programmes. Her research interests include pricing and revenue management, design and evaluation of reliable networks, metaheuristics for combinatorial optimization, facility location problems. Her research articles have been published in journals such as Omega - the International Journal of Management Science, Journal of Revenue and Pricing Management, IEEE Transactions on Reliability, Opsearch, Indore Management Journal, Calcutta Statistical Association Bulletin. Sumanta Basu is an Associate Professor of Operations Management at Indian Institute of Management Calcutta. He holds a FPM degree in Production and Quantitative Methods, Indian Institute of Management Ahmedabad and a B.Tech (Hons.) in Chemical Engineering from Vidyasagar University. His primary research interests are in operations and supply chain management, operations research, and pricing and revenue management, etc. He has six years of work experience in petrochemicals industry and in IT industry before joining academics. He has published papers in journals like Omega, Journal of Revenue and Pricing Management, OPSEARCH, American Journal of Operations Research, Decision etc. He has two US patents and one US patent application on his name for process improvements in BPO industry in collaboration with Wipro Technologies.

396© IEOM Society International

Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, March 8-10, 2016

Partha Sarathi Ghosh is currently associated with Cognizant Technology Solutions, India and working in Life Science R&D sector with in Cognizant. He is having 9 years of industrial experience. He finished his studies in Computer Application in India, 2007.His research interests center on machine learning, hybrid meta heuristics and variants of facility location problem.

397© IEOM Society International