Examinando por Autor "Herrán, Alberto"

Mostrando 1 - 3 de 3

A GRASP method for the Bi-Objective Multiple Row Equal Facility Layout Problem
(Elsevier, 2024-06-22) Uribe, Nicolás R.; Herrán, Alberto; Colmenar, J. Manuel
The Bi-Objective Multiple Row Equal Facility Layout Problem considers both quantitative and qualitative objectives that are very useful in many scenarios like the factory design. In this work, a new multi-objective GRASP approach is proposed which applies an ensemble of four different constructive methods followed by the combination of two local search procedures, improving the results from the state of the art. Due to the superiority of this proposal, a new dataset of larger problem instances is generated, providing detailed metrics of the obtained solutions
Multi-objective Optimization in Diversity Problems
(Springer Nature, 2023-11-17) Manuel Colmenar, Jose Manuel; Herrán, Alberto; Martín-Santamaría, Raúl
Diversity problems are usually studied from a single-objective point of view. However, two or more diversity functions could present opposite or divergent behavior, which requires a multi-objective point of view. To illustrate this kind of problems, this chapter presents the study of the bi-objective diversity problem (BODP), which considers the MaxSum and the MaxMin as objective functions to simultaneously maximize. Six different multi-objective algorithms have been described, analyzing their results on six performance metrics using a subset of instances from the MDPLIB 2.0 library.
Path relinking strategies for the bi-objective double floor corridor allocation problem
(Elsevier, 2024-12-03) Uribe, Nicolás R.; Herrán, Alberto; Colmenar, J. Manuel
The bi-objective Double Floor Corridor Allocation Problem is an operational research problem with the goal of finding the best arrangement of facilities in a layout with two corridors located in two floors, in order to minimize the material handling costs and the corridor length. In this paper, we present a novel approach based on a combination of Path Relinking strategies. To this aim, we propose two greedy algorithms to produce an initial set of non-dominated solutions. In a first stage, we apply an Interior Path Relinking with the aim of improving this set and, in the second stage, apply an Exterior Path Relinking to reach solutions that are unreachable in the first stage. Our extensive experimental analysis shows that our method, after automatic parameter optimization, completely dominates the previous benchmarks, spending shorter computation times. In addition, we provide detailed results for the new instances, including standard metrics for multi-objective problems