A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

Sánchez‐Oro, Jesús; López-Sánchez, Ana Dolores; Martı́nez-Gavara, Anna; Hernández-Díaz, Alfredo G.; Duarte, Abraham

doi:10.3390/math9080853

Cited by 4 publications

(2 citation statements)

References 53 publications

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“…The authors illustrated the effectiveness of their method, using multiobjective FLPs with coverage, median, and center objectives. Likewise, in Sánchez-Oro et al (2021) a hybrid metaheuristic combining strategic oscillation with PR for the solution of a multiobjective k-balanced center location problem was introduced. In a novel approach, PR was used to repair infeasible solutions obtained during the strategic oscillation.…”

Section: Path-relinking Algorithmmentioning

confidence: 99%

A facility location problem for extracurricular workshop planning: bi‐level model and metaheuristics

Polino,

Camacho‐Vallejo,

Villegas

2023

Int Trans Operational Res

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This paper presents a facility location problem with capacitated multiservice facilities in which the allocation of the users is based on their preferences. The problem arises from an educational program, where a government agency or a nongovernmental organization (NGO) offers extracurricular workshops to elementary school students. These workshops promote the development of academic, social, or cultural skills of the students. This problem is formulated as a bi‐level program. The government/NGO is associated with the upper level, which aims to minimize the costs for opening workshops in different schools and the costs of allocating students to each workshop. The lower level is related to the students and seeks to optimize their global preferences for the offered workshops. To solve this problem, we propose a single‐level reformulation and two metaheuristics (a path‐relinking metaheuristic (PRM) and an iterated local search (ILS) procedure). The best performing method is the PRM that generates saturated initial random solutions following a drop heuristic approach. After different phases of improvement (with drop and exchange heuristics), the solutions undergo a path‐relinking procedure. The trajectory between the initial solution and the best solution found so far is explored using a randomized backward path‐relinking strategy that thoroughly explores the neighborhood of the best solution. Computational experimentation indicates that the proposed PRM metaheuristic is effective and efficient. The results obtained provide better upper bounds in shorter running times than the ones obtained by the single‐level reformulation or the ILS procedure. Finally, the application to a realistic case study of Apodaca municipality in Nuevo Leon, Mexico, shows that large‐scale instances can be solved efficiently using the proposed metaheuristic.

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Section: Path-relinking Algorithmmentioning

confidence: 99%

A facility location problem for extracurricular workshop planning: bi‐level model and metaheuristics

Polino,

Camacho‐Vallejo,

Villegas

2023

Int Trans Operational Res

View full text Add to dashboard Cite

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“…The paper by Sánchez Oro et at. [1] presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.…”

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confidence: 99%

Special Issue “Recent Advances and Applications in Multi Criteria Decision Analysis”

Jiménez-Martín

2022

Mathematics

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Over the last few decades, Multi-criteria Decision Analysis (MCDA) techniques have been successfully applied to complex decision-making problems in a wide range of fields, such as economics, finance, logistics, environmental restoration, health or industrial organization, to name but a few, and imprecision and uncertainty have been incorporated into the decision-making process and applied to group decision-making contexts. [...]

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Fixed set search applied to the multi-objective minimum weighted vertex cover problem

2022

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The Fixed Set Search (FSS) is a novel metaheuristic that adds a learning mechanism to the Greedy Randomized Adaptive Search Procedure (GRASP). In recent publications, its efficiency has been shown on different types of combinatorial optimization problems like routing, machine scheduling and covering. In this paper the FSS is adapted to multi-objective problems for finding Pareto Front approximations. This adaptation is illustrated for the bi-objective Minimum Weighted Vertex Cover Problem (MWVCP). In this work, a simple and effective bi-objective GRASP algorithm for the MWVCP is developed in the first stage. One important characteristic of the proposed GRASP is that it avoids the use of weighted sums of objective functions in the local search and the greedy algorithm. In the second stage, the bi-objective GRASP is extended to the FSS by adding a learning mechanism adapted to multi-objective problems. The conducted computational experiments show that the proposed FSS and GRASP algorithm significantly outperforms existing methods for the bi-objective MWVCP. To fully evaluate the learning mechanism of the FSS, it is compared to the underlying GRASP algorithm on a wide range of performance indicators related to convergence, distribution, spread and cardinality.

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A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

Cited by 4 publications

References 53 publications

A facility location problem for extracurricular workshop planning: bi‐level model and metaheuristics

A facility location problem for extracurricular workshop planning: bi‐level model and metaheuristics

Special Issue “Recent Advances and Applications in Multi Criteria Decision Analysis”

Fixed set search applied to the multi-objective minimum weighted vertex cover problem

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