Distributionally robust facility location problem under decision-dependent stochastic demand

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Başçiftçi, Beste and Ahmed, Shabbir and Shen, Siqian (2021) Distributionally robust facility location problem under decision-dependent stochastic demand. European Journal of Operational Research, 292 (2). pp. 548-561. ISSN 0377-2217 (Print) 1872-6860 (Online)

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Abstract

While the traditional facility location problem considers exogenous demand, in some applications, locations of facilities could affect the willingness of customers to use certain types of services, e.g., carsharing, and therefore they also affect realizations of random demand. Moreover, a decision maker may not know the exact distribution of such endogenous demand and how it is affected by location choices. In this paper, we consider a distributionally robust facility location problem, in which we interpret the moments of stochastic demand as functions of facility-location decisions. We reformulate a two-stage decision-dependent distributionally robust optimization model as a monolithic formulation, and then derive exact mixed-integer linear programming reformulation as well as valid inequalities when the means and variances of demand are piecewise linear functions of location solutions. We conduct extensive computational studies, in which we compare our model with a decision-dependent deterministic model, as well as stochastic programming and distributionally robust models without the decision-dependent assumption. The results show superior performance of our approach with remarkable improvement in profit and quality of service under various settings, in addition to computational speed-ups given by formulation enhancements. These results draw attention to the need of considering the impact of location decisions on customer demand within this strategic-level planning problem.
Item Type: Article
Uncontrolled Keywords: Decision-dependent uncertainty; Distributionally robust optimization; Facility location; Mixed-integer linear programming; Uncertainty modeling
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: Beste Başçiftçi
Date Deposited: 19 Aug 2022 14:26
Last Modified: 19 Aug 2022 14:26
URI: https://research.sabanciuniv.edu/id/eprint/43256

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