Examinando por Autor "Herrán, Alberto"

Mostrando 1 - 7 de 7

A Basic Variable Neighborhood Search approach for the Bi-Objective Multi-Row Equal Facility Layout Problem
(Springer, 2023-05-29) R. Uribe, Nicolás; Herrán, Alberto; Colmenar, J. Manuel
The Bi-Objective Multi-Row Facility Layout Problem is a problem belonging to the family of Facility Layout Problems. This problem is challenging for exact and metaheuristics approaches. We use the Pareto front approach instead of the weight approach by means of a non-dominated solution set which we update in order to keep only the non-dominated solutions. To tackle this problem, we propose a Basic VNS algorithm based on a constructive method that generates random solutions, a mono-objective local search that relies on an interchange move, and a shake method that applies insert moves. In this regard, we also explain how to adapt the mono-objective schema of the BVNS for a multi-objective one. Then, we compare our results with the state of the art and propose future work.
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
A Path Relinking-based approach for the Bi-Objective Double Floor Corridor Allocation Problem
(Springer, 2024-06-12) R. Uribe, Nicolás; Herrán, Alberto; Colmenar, J. Manuel
The Bi-Objective Double Floor Corridor Allocation Problem is one of the most recent incorporation to the family of Facility Layout Problems. This problem, which has been a challenge for exact and metaheuristic approaches, involves optimizing the layout of the given facilities to minimize material handling cost and the length of the corridor considering more than one floor. This paper introduces a new approach based on the combination of two greedy methods and a path relinking implementation to tackle this problem. The experimental results show the superiority of our proposal in relation to the current state-of-the-art under different multi-objective metrics.
An improved GRASP method for the Multiple Row Equal Facility Layout Problem
(Elsevier, 2021-11-15) R. Uribe, Nicolás; Herrán, Alberto; Colmenar, J. Manuel; Duarte, Abraham
As it is well documented in the literature, an effective facility layout design of a company significantly increases throughput, overall productivity, and efficiency. Symmetrically, a poor facility layout results in increased work-in process and manufacturing lead time. In this paper we focus on the Multiple Row Equal Facility Layout Problem (MREFLP) which consists in locating a given set of facilities in a layout where a maximum number of rows is fixed. We propose a Greedy Randomized Adaptive Search Procedure (GRASP), with an improved local search that relies on an efficient calculation of the objective function, and a probabilistic strategy to select those solutions that will be improved. We conduct a through preliminary experimentation to investigate the influence of the proposed strategies and to tune the corresponding search parameters. Finally, we compare our best variant with current state-of-the-art algorithms over a set of 552 diverse instances. Experimental results show that the proposed GRASP finds better results spending much less execution time.
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
Two-phase GRASP for the Multi-Constraint Graph Partitioning problem
(Elsevier, 2025-04) Herrán, Alberto; Colmenar, J. Manuel; Resende, Mauricio G.C.
The Multi-Constraint Graph Partitioning (MCGP) problem seeks a partition of the node set of a graph into a fixed number of clusters such that each cluster satisfies a collection of node-weight constraints and the total cost of the edges whose end nodes are in the same cluster is minimized. In this paper we propose a two-phase reactive GRASP heuristic to find near-optimal solutions to the MCGP problem. Our proposal is able to reach all the best known results for state-of-the-art instances, obtaining all the certified optimum values while spending only a fraction of the time in relation to the previous methods. To reach these results we have implemented an efficient computation method applied in the improvement phase. Besides, we have created a new set of larger instances for the MCGP problem and provided detailed results for future comparisons