Javier Alcaraz (University Miguel Hernández of Elche), Mercedes Landete (University Miguel Hernández of Elche), Juan F. Monge (University Miguel Hernández of Elche) and José L. Sainz-Pardo (University Miguel Hernández of Elche).
Abstract: Some location problems with unreliable facilities present two different objectives, one consisting of minimizing the opening and transportation costs if none of the facilities fail and another consisting of minimizing the expected transportation costs. Usually, these different targets are combined in a single objective function and the decision maker can obtain some different solutions weighting both objectives. However, if the decision maker prefers to obtain a diverse set of non-dominated optimal solutions, then such procedure would not be effective. We have designed and implemented two multi-objective evolutionary algorithms for the realibility fixed-charge location problem by exploiting the peculiarities of this problem in order to obtain sets of solutions that are properly distributed along the Pareto-optimal frontier. The computational results demonstrate the outstanding efficiency of the proposed algorithms, although they present clear differences.
Keywords: Location; Multi-objective location problems; Reliability models; Pareto frontier; Multi-objective evolutionary algorithms; Metaheuristics.
Scientific articles
N. Allouch, Luis A. Guardiola, & A. Meca (2024). Measuring productivity in networks: A game-theoretic approach. Socio-Economic Planning Sciences, 91, 101783.
N. Allouch (University of Kent – School of Economics), Luis A. Guardiola (Departamento de Métodos Cuantitativos para la Economía y Empresa, Universidad de Murcia), Ana Meca (I.U. Centro de Investigación Operativa, Universidad Miguel Hernández de Elche) Abstract: Measuring individual productivity (or equivalently distributing the overall productivity) in a network structure of workers displaying peer effects has been [...]