A Multi-Objective Parallel Iterated Greedy for Solving the p-Center and p-Dispersion Problem

Resumen

This paper generalizes the iterated greedy algorithm to solve a multi-objective facility location problem known as the Bi-objective p-Center and p-Dispersion problem ( BpCD ). The new algorithm is coined as Multi-objective Parallel Iterated Greedy (MoPIG) and optimizes more than one objective at the same time. The BpCD seeks to locate p facilities to service or cover a set of n demand points, and the goal is to minimize the maximum distance between facilities and demand points and, at the same time, maximize the minimum distance between all pairs of selected facilities. Computational results demonstrate the effectiveness of the proposed algorithm over the evolutionary algorithms NSGA-II, MOEA/D, and the Strength Pareto Evolutionary Algorithm 2 (SPEA2), comparing them with the optimal solution found by the ϵ -constraint method.

Sergio Pérez-Peló

Doctor en Inteligencia Artificial

Estudiante de doctorado en la Universidad Rey Juan Carlos

Jesús Sánchez-Oro

Profesor Titular de Universidad

Profesor Titular del Departamento de Informática, siendo uno de los investigadores principales del Grupo de Investigación de Algoritmos para la Optimización GRAFO.

Abraham Duarte

Catedrático de Universidad

Mi carrera investigadora se ha centrado en el desarrollo de nuevos algoritmos y técnicas de Inteligencia Computacional (metaheurísticas) y su aplicación a diferentes problemas en Ciencia e Ingeniería desde que me incorporé a la Universidad Rey Juan Carlos (URJC) en el octubre del año 2000.