Examinando por Autor "Colmenar, J. Manuel"

Mostrando 1 - 5 de 5

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
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.
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