Examinando por Autor "Colmenar, J. Manuel"

Mostrando 1 - 9 de 9

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.
Un algoritmo memético para la ubicación de instalaciones desagradables en el plano con tamaño variable.
(2024-06) Cordón, Oscar; Colmenar, J. Manuel; Salazar, Sergio
La ubicación de instalaciones desagradables (obnoxious) es un problema de optimización con un gran impacto social. En concreto, el problema de la ubicación de instalaciones desagradables en el plano con tamaño variable (OPPMVS) estudia la ubicación de instalaciones considerando que el efecto nocivo se transmite a través del aire y depende de la producción o servicio de la instalación. En este trabajo se propone un algoritmo memético donde la generación de la población inicial y los operadores genéticos se han diseñado específicamente para el problema objetivo. En esta primera aproximación sobre este problema continuo se han obtenido resultados competitivos respecto al estado del arte, identificando diferentes puntos de mejora para trabajos futuros.
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.
Changeover minimization in the production of metal parts for car seats
(Elsevier, 2024-10-16) Colmenar, J. Manuel; Laguna, Manuel; Martín-Santamaría, Raúl
We tackle a capacitated lot-sizing and scheduling problem (CLSP) with the main objective of minimizing changeover time in the production of metal parts for car seats. Changeovers occur when a machine (or production line) is reconfigured to produce a different product or part, leading to production downtime and loss of efficiency. In this study, we first provide a mixed-integer programming (MIP) formulation of the problem. We test the limits of solving the problem with commercial mathematical programming software. We also propose two approaches to tackle instances found in practice for which the mathematical programming model is not a viable solution method. Both approaches are based on partitioning the entire production of a part into production runs (or work slots). In the first approach, the work slots are assigned to machines and sequenced by a metaheuristic that follows the search principles of the GRASP (greedy randomized adaptive procedure) and VNS (variable neighborhood search) methodologies. In the second approach, we develop a Hexaly Optimizer (formerly known as LocalSolver) model to assign and sequence work slots. The study provides insights into how to minimize changeovers and improve production efficiency in metal parts manufacturing for car seats. The findings of this study have practical implications for the auto-part manufacturing industry, where efficient and cost-effective production is critical to meet the demands of the market
On the automatic generation of metaheuristic algorithms for combinatorial optimization problems
(Elsevier, 2024) Martín-Santamaría, Raúl; López-Ibáñez, Manuel; Stützle, Thomas; Colmenar, J. Manuel
Metaheuristic algorithms have become one of the preferred approaches for solving optimization problems. Finding the best metaheuristic for a given problem is often difficult due to the large number of available approaches and possible algorithmic designs. Moreover, high-performing metaheuristics often combine general-purpose and problem-specific algorithmic components. We propose here an approach for automatically designing metaheuristics using a flexible framework of algorithmic components, from which algorithms are instantiated and evaluated by an automatic configuration method. The rules for composing algorithmic components are defined implicitly by the properties of each algorithmic component, in contrast to previous proposals, which require a handwritten algorithmic template or grammar. As a result, extending our framework with additional components, even problem-specific or user-defined ones, automatically updates the design space. Furthermore, since the generated algorithms are made up of components, they can be easily interpreted. We provide an implementation of our proposal and demonstrate its benefits by outperforming previous research in three distinct problems from completely different families: a facility layout problem, a vehicle routing problem and a clustering problem.
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