Combinatorial Optimization Problems and Metaheuristics: Review, Challenges, Design, and Development

In the past few decades, metaheuristics have demonstrated their suitability in addressing complex problems over different domains. This success drives the scientific community towards the definition of new and better-performing heuristics and results in an increased interest in this research field....

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Bibliographic Details
Published in:Applied sciences Vol. 11; no. 14; p. 6449
Main Authors: Peres, Fernando, Castelli, Mauro
Format: Journal Article
Language:English
Published: Basel MDPI AG 13.07.2021
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ISSN:2076-3417, 2076-3417
Online Access:Get full text
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Summary:In the past few decades, metaheuristics have demonstrated their suitability in addressing complex problems over different domains. This success drives the scientific community towards the definition of new and better-performing heuristics and results in an increased interest in this research field. Nevertheless, new studies have been focused on developing new algorithms without providing consolidation of the existing knowledge. Furthermore, the absence of rigor and formalism to classify, design, and develop combinatorial optimization problems and metaheuristics represents a challenge to the field’s progress. This study discusses the main concepts and challenges in this area and proposes a formalism to classify, design, and code combinatorial optimization problems and metaheuristics. We believe these contributions may support the progress of the field and increase the maturity of metaheuristics as problem solvers analogous to other machine learning algorithms.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app11146449