Fuzzy Bicriteria Optimization Approach to Distribution Network Design Santiago García-Carbajal, Antonio Palacio, Belarmino Adenso-Díaz and Sebastián Lozano Abstract Distribution network design deals with defining which elements will be part of the supply chain and how they will be interrelated. Many authors have studied this problem from a cost minimization point of view. Nowadays the sustainability factor is increasing its importance in the logistics operations and must be considered in the design process. We deal here with the problem of determining the location of the links in a supply chain and the assignment of the final customers considering at the same time cost and environmental objectives. We use a fuzzy bicriteria model for solving the problem, embedded in a genetic algorithm that looks for the best trade-off solution. A set of experiments have been carried out to check the performance of the procedure, using some instances for which we know a priori a good reference solution. 1 Introduction The fierce competition between the different supply chains makes it necessary that efficiency be continuously pursued. One of the most important strategic decisions, and one that has a long-term impact in the economic results of the logistics operations, is the design of the distribution network. Distribution network design is the process of determining the structure of a supply chain, defining which elements will be part of it (i.e., where locate the facilities), and what will be the interrelationships between them (i.e., the allocation of customers to facilities and how the material and products will flow in the network between the nodes in the network). For that reason the problem is often called location-allocation (e.g. [1]). S. García-Carbajal · A. Palacio · B. Adenso-Díaz Escuela Politécnica Superior de Ingeniería de Gijón, Universidad de Oviedo, 33003 Oviedo, Asturias, Spain S. Lozano (B ) Escuela Superior de Ingenieros, Universidad de Sevilla, 41092 Seville, Spain e-mail: slozano@us.es © Springer International Publishing Switzerland 2015 S. Fidanova (ed.), Recent Advances in Computational Optimization, Studies in Computational Intelligence 580, DOI 10.1007/978-3-319-12631-9_2 21