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Facility Location with Competition or Decision-dependent Uncertainty: Models, Algorithms and Extensions, February 18, 2022

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Attend the next IE Decision Systems Engineering Spring 2022 Seminar Series event with University of Michigan Associate Professor Siquan Shen, who discusses strategic planning for customer demand and facilities.

Facility Location with Competition or Decision-dependent Uncertainty: Models, Algorithms and Extensions
Presented by Siqian Shen, University of Michigan

Friday, February 18, 2022
Noon–1 p.m.
Attend on Zoom

Abstract

Facility location models are ubiquitously involved in modern transportation and logistics problems. We present recent results of two types of facility-location models that involve (i) competition and probabilistic customer choice or (ii) location-dependent uncertain demand with ambiguously known distribution.

For (i), we study a Stackelberg game that admits a bilevel mixed-integer nonlinear program (MINLP) formulation, and derive an equivalent, single-level MINLP reformulation and exploit the problem structures to derive valid inequalities based on submodularity and concave overestimation, respectively. We also study various model extensions by considering general facility setup costs, outside competitors as well as other types of decisions for planning facilities. We conduct numerical studies to demonstrate that the exact algorithm significantly accelerates the computation of CFLP on large-sized instances that have not been solved optimally or even heuristically by existing methods.

For (ii), we represent moment information of stochastic demand as piecewise linear functions of location decisions, and then develop an exact mixed-integer linear programming reformulation of a decision-dependent distributionally robust optimization model. Our results draw attention to the need of considering various impacts of competition and location choices on customer demand within the strategic-level facility planning problem.

About the speaker

Siqian Shen is an associate professor and Wilson Faculty Fellow in the Department of Industrial and Operations Engineering at the University of Michigan. She also serves as an associate director in the Michigan Institute for Computational Discovery and Engineering (MICDE).

She obtained a Bachelor of Science degree from Tsinghua University in 2007 and a doctorate from the University of Florida in 2011. Her theoretical research interests are in integer programming, stochastic/robust optimization and network optimization. Applications for her work include optimization and risk analysis of energy, health care, cloud computing and transportation systems.

She is a recipient of the IEE Pritsker Doctoral Dissertation Award, IBM Smarter Planet Innovation Faculty Award, and the Department of Energy Early Career Award. She serves on the editorial board of several journals including IISE Transactions, Networks, INFORMS Journal on Computing, Transportation Science, Manufacturing and Service Operations Management, Service Science, and the European Journal of Operational Research.

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