0000000000217791

AUTHOR

Dario Landa-silva

0000-0002-9499-6827

showing 2 related works from this author

Randomized heuristics for the Capacitated Clustering Problem

2017

In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memory-based method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent l…

MatheuristicMathematical optimizationInformation Systems and Management0211 other engineering and technologies02 engineering and technologyCapacitated ClusteringTheoretical Computer ScienceArtificial Intelligence0202 electrical engineering electronic engineering information engineeringLocal search (optimization)Cluster analysisGreedy randomized adaptive search procedureMathematicsGrasp021103 operations researchbusiness.industryHeuristicGRASPGraph partitioningGraph partitionComputer Science ApplicationsControl and Systems EngineeringSimulated annealing020201 artificial intelligence & image processingHeuristicsbusinessSoftware
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Selecting Genetic Operators to Maximise Preference Satisfaction in a Workforce Scheduling and Routing Problem

2017

The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising both operational costs and travelling distance. This study seeks to determine effective combinations of genetic operators combined with heuristics that help to find good solutions for this constrained combinatorial optimisation problem. In particular, it aims to identify the best set of operators that help to maximise customers and workers preferences satisfaction. This paper advances the understand…

Mathematical optimizationWorkforce scheduling021103 operations researchComputer science0211 other engineering and technologiesScheduling (production processes)02 engineering and technologyPreference satisfactionHome healthWorkforce0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingOperational costsHeuristicsProceedings of the 6th International Conference on Operations Research and Enterprise Systems
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