0000000000082656

AUTHOR

Jesús Sánchez-oro

showing 11 related works from this author

Greedy randomized adaptive search procedure with exterior path relinking for differential dispersion minimization

2015

We propose several new hybrid heuristics for the differential dispersion problem, the best of which consists of a GRASP with sampled greedy construction with variable neighborhood search for local improvement. The heuristic maintains an elite set of high-quality solutions throughout the search. After a fixed number of GRASP iterations, exterior path relinking is applied between all pairs of elite set solutions and the best solution found is returned. Exterior path relinking, or path separation, a variant of the more common interior path relinking, is first applied in this paper. In interior path relinking, paths in the neighborhood solution space connecting good solutions are explored betwe…

Mathematical optimizationInformation Systems and ManagementHeuristic (computer science)GRASPComputer Science ApplicationsTheoretical Computer ScienceSet (abstract data type)Artificial IntelligenceControl and Systems EngineeringPath (graph theory)MinificationHeuristicsSoftwareVariable neighborhood searchGreedy randomized adaptive search procedureMathematicsInformation Sciences
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Variable Neighborhood Search for the Vertex Separation Problem

2012

The vertex separation problem belongs to a family of optimization problems in which the objective is to nd the best separator of vertices or edges in a generic graph. This optimization problem is strongly related to other well-known graph problems; such as the Path-Width, the Node Search Number or the Interval Thickness, among others. All of these optimization problems are NP-hard and have practical applications in VLSI, computer language compiler design or graph drawing. Up to know, they have been generally tackled with exact approaches, presenting polynomial-time algorithms to obtain the optimal solution for speci c types of graphs. However, in spite of their practical applications, these…

InformáticaMathematical optimizationOptimization problemGeneral Computer Sciencebusiness.industryVariable Neigborhood SearchVertex coverMetaheuristicsManagement Science and Operations Research5207.10 Estadísticas de PoblacionesLayout ProblemsGraph drawingModeling and Simulation52 DemografíaCombinatorial OptimizationCombinatorial optimizationEstadística y DemografíaFeedback vertex setLocal search (optimization)1203.17 InformáticabusinessMetaheuristicVariable neighborhood searchMathematics
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A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

2021

This paper 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. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. 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.

Mathematical optimizationComputer scienceGeneral Mathematics0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyMulti-objective optimizationSet (abstract data type)path relinkingDiscrete optimization0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Center (algebra and category theory)multiobjective optimizationEngineering (miscellaneous)021103 operations researchOscillationlcsh:MathematicsWorkload<i>k</i>-balanced problemGreedy Randomized Adaptive Search Procedure (GRASP)lcsh:QA1-939strategic oscillationPath (graph theory)020201 artificial intelligence & image processingdiscrete optimization<i>k</i>-center problemMathematics
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GRASP with path relinking for the orienteering problem

2014

In this paper, we address an optimization problem resulting from the combination of the well-known travelling salesman and knapsack problems. In particular, we target the orienteering problem, originated in the context of sport, which consists of maximizing the total score associated with the vertices visited in a path within the available time. The problem, also known as the selective travelling salesman problem, is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in routing and tourism. We propose a heuristic method—based on the Greedy Randomized Adapt…

MarketingMathematical optimization021103 operations researchOptimization problembusiness.industryHeuristic (computer science)Strategy and Management0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchTravelling salesman problemManagement Information SystemsKnapsack problemShortest path problem0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingLocal search (optimization)businessMetaheuristicGreedy randomized adaptive search procedureMathematicsJournal of the Operational Research Society
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Iterated greedy with variable neighborhood search for a multiobjective waste collection problem

2020

Abstract In the last few years, the application of decision making to logistic problems has become crucial for public and private organizations. Efficient decisions clearly contribute to improve operational aspects such as cost reduction or service improvement. The particular case of waste collection service considered in this paper involves a set of economic, labor and environmental issues that translate into difficult operational problems. They pose a challenge to nowadays optimization technologies since they have multiple constraints and multiple objectives that may be in conflict. We therefore need to resort to multiobjective approaches to model and solve this problem, providing efficie…

0209 industrial biotechnologyService (systems architecture)Mathematical optimizationComputer sciencemedia_common.quotation_subjectGeneral EngineeringWaste collection02 engineering and technologyMulti-objective optimizationComputer Science ApplicationsSet (abstract data type)020901 industrial engineering & automationArtificial Intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingIterated greedyFunction (engineering)Variable neighborhood searchmedia_commonExpert Systems with Applications
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Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies

2015

International audience; Embedded systems have become an essential part of our lives, thanks to their evolution in the recent years, but the main drawback is their power consumption. This paper is focused on improving the memory allocation of embedded systems to reduce their power consumption. We propose a parallel variable neighborhood search algorithm for the dynamic memory allocation problem, and compare it with the state of the art. Computational results and statistical tests applied show that the proposed algorithm produces significantly better outcomes than the previous algorithm in shorter computing time.

Mathematical optimizationparallelismmetaheuristicsC dynamic memory allocationComputer sciencebusiness.industryApplied Mathematics[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Static memory allocationPower consumptionEmbedded systemDiscrete Mathematics and Combinatoricsdynamic memory allocation problemembedded systemsState (computer science)businessMetaheuristicvariable neighborhood searchVariable neighborhood searchDrawbackStatistical hypothesis testing
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Tabu search for the dynamic Bipartite Drawing Problem

2018

Abstract Drawings of graphs have many applications and they are nowadays well-established tools in computer science in general, and optimization in particular. Project scheduling is one of the many areas in which representation of graphs constitutes an important instrument. The experience shows that the main quality desired for drawings of graphs is readability, and crossing reduction is a fundamental aesthetic criterion to achieve it. Incremental or dynamic graph drawing is an emerging topic in this context, where we seek to preserve the layout of a graph over successive drawings. In this paper, we target the edge crossing reduction in the context of incremental graph drawing. Specifically…

Theoretical computer scienceGeneral Computer ScienceComputer sciencebusiness.industryHeuristic020207 software engineering02 engineering and technologyManagement Science and Operations ResearchMachine learningcomputer.software_genreGraphTabu searchGraph drawingModeling and SimulationClique-width0202 electrical engineering electronic engineering information engineeringBipartite graph020201 artificial intelligence & image processingForce-directed graph drawingArtificial intelligencebusinesscomputerGraph productComputers &amp; Operations Research
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A review on discrete diversity and dispersion maximization from an OR perspective

2022

Abstract The problem of maximizing diversity or dispersion deals with selecting a subset of elements from a given set in such a way that the distance among the selected elements is maximized. The definition of distance between elements is customized to specific applications, and the way that the overall diversity of the selected elements is computed results in different mathematical models. Maximizing diversity by means of combinatorial optimization models has gained prominence in Operations Research (OR) over the last two decades, and constitutes nowadays an important area. In this paper, we review the milestones in the development of this area, starting in the late eighties when the first…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceMathematical modelHeuristicComputer scienceMaximizationManagement Science and Operations ResearchRepresentativeness heuristicIndustrial and Manufacturing EngineeringSet (abstract data type)Modeling and SimulationBenchmark (computing)Combinatorial optimizationDiversity (business)European Journal of Operational Research
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Scatter search for the profile minimization problem

2014

We study the problem of minimizing the profile of a graph and develop a solution method by following the tenets of scatter search. Our procedure exploits the network structure of the problem and includes strategies that produce a computationally efficient and agile search. Among several mechanisms, our search includes path relinking as the basis for combining solutions to generate new ones. The profile minimization problem PMP is NP-Hard and has relevant applications in numerical analysis techniques that rely on manipulating large sparse matrices. The problem was proposed in the early 1970s but the state-of-the-art does not include a method that could be considered powerful by today's compu…

Mathematical optimizationBasis (linear algebra)ExploitComputer Networks and CommunicationsComputer scienceNumerical analysisHardware and ArchitecturePath (graph theory)Graph (abstract data type)MetaheuristicSoftwareInformation SystemsSparse matrixEnvelope (motion)Networks
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Optimization procedures for the bipartite unconstrained 0-1 quadratic programming problem

2014

The bipartite unconstrained 0-1 quadratic programming problem (BQP) is a difficult combinatorial problem defined on a complete graph that consists of selecting a subgraph that maximizes the sum of the weights associated with the chosen vertices and the edges that connect them. The problem has appeared under several different names in the literature, including maximum weight induced subgraph, maximum weight biclique, matrix factorization and maximum cut on bipartite graphs. There are only two unpublished works (technical reports) where heuristic approaches are tested on BQP instances. Our goal is to combine straightforward search elements to balance diversification and intensification in bot…

Discrete mathematicsGeneral Computer ScienceIterated local searchMaximum cutInduced subgraphManagement Science and Operations ResearchComplete bipartite graphCombinatoricsBQPModeling and SimulationBipartite graphBeam searchQuadratic programmingMathematicsofComputing_DISCRETEMATHEMATICSMathematicsComputers &amp; Operations Research
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Variable neighborhood descent for the incremental graph drawing

2017

Abstract Graphs are used to represent reality in several areas of knowledge. Drawings of graphs have many applications, from project scheduling to software diagrams. The main quality desired for drawings of graphs is readability, and crossing reduction is a fundamental aesthetic criterion for a good representation of a graph. In this paper we target the edge crossing reduction in the context of incremental graph drawing, in which we want to preserve the layout of a graph over successive drawings. We propose a hybrid method based on the GRASP (Greedy Randomized Adaptive Search Procedure) and VND (Variable Neighborhood Descent) methodologies and compare it with previous methods via simulation.

021103 operations researchTheoretical computer sciencebusiness.industryApplied MathematicsGRASP0211 other engineering and technologies010103 numerical & computational mathematics02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesReadabilitySoftwareGraph drawingDiscrete Mathematics and CombinatoricsArtificial intelligenceForce-directed graph drawing0101 mathematicsbusinessGraph operationsMetaheuristiccomputerGreedy randomized adaptive search procedureMathematicsofComputing_DISCRETEMATHEMATICSMathematicsElectronic Notes in Discrete Mathematics
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