RT info:eu-repo/semantics/article
T1 A greedy randomized adaptive search with probabilistic learning for solving the uncapacitated plant cycle location problem
A1 López Plata, Israel
A1 Expósito Izquierdo, Cristofer Juan
A1 Lalla Ruiz, Eduardo
A1 Melián Batista, María Belén
A1 Moreno Vega, José Marcos
A2 Ingeniería Informática y de Sistemas
K1 Greedy Randomized Adaptive Search Procedure
K1 Probabilistic Learning Model
K1 Uncapacitated Plant Cycle Location Problem
AB In this paper, we address the Uncapacitated Plant Cycle Location Problem. It is a location-routing problem aimed at determining a subset of locations to set up plants dedicated to serving customers. We propose a mathematical formulation to model the problem. The high computational burden required by the formulation when tackling large scenarios encourages us to develop a Greedy Randomized Adaptive Search Procedure with Probabilistic Learning Model. Its rationale is to divide the problem into two interconnected sub-problems. The computational results indicate the high performance of our proposal in terms of the quality of reported solutions and computational time. Specifically, we have overcome the best approach from the literature on a wide range of scenarios.
YR 2022
FD 2022
LK http://riull.ull.es/xmlui/handle/915/40318
UL http://riull.ull.es/xmlui/handle/915/40318
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 18-dic-2024