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2225. Solution approaches for multi-source capacitated facility location problems with fairness objectives

Invited abstract in session TA-26: Applications to Logistics and Transportation, stream Combinatorial Optimization.

Tuesday, 8:30-10:00
Room: 012 (building: 208)

Authors (first author is the speaker)

1. Gianfranco Guastaroba
Department of Economics and Management, University of Brescia
2. Carlo Filippi
Dept. of Economics and Management, University of Brescia
3. Juan José Salazar González
Estadística e Investigación Operativa, Universidad de La Laguna (Tenerife)

Abstract

Modern societies are developing an ever-increasing concern toward issues related to equity, often synonymously called fairness. In location problems, scholars soon realized the importance of incorporating equity in siting decision models. Often a decision-maker has to locate a set of facilities, which provide a service (or good) and are reached by customers at their own costs. In such situations, improving system efficiency requires minimizing the average cost paid by customers to reach a facility, while improving fairness requires minimizing the variability in the cost distribution. The latter is especially relevant in the public sector, where providing customers with a fair access is a crucial concern. We measure accessibility fairness by using the conditional beta-mean, which can be intuitively defined as the average distance traveled by beta% of the customers that travel the longest distances to reach the assigned facility. We show that incorporating such measure into a classic multi-source CFLP leads to a non-linear MIP. Borrowing some ideas from bilevel programming, we propose two linear reformulations of the latter MIP, and develop two solution methods that work along the general lines of a cutting-plane algorithm. Computational experiments show the effectiveness of the solution methods proposed. Further, a trade-off analysis between efficiency and fairness show that the proposed approaches may be used as managerial tools to balance these two objectives.

Keywords

Status: accepted

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