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Combinatorial optimization problems and metaheuristics
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| 3.28 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
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.
Descrição
Peres, F., & Castelli, M. (2021). Combinatorial optimization problems and metaheuristics: Review, challenges, design, and development. Applied Sciences (Switzerland), 11(14), 1-39. [6449]. https://doi.org/10.3390/app11146449
Palavras-chave
Combinatorial optimization problems Framework Metaheuristic Standardization General Materials Science Instrumentation General Engineering Process Chemistry and Technology Computer Science Applications Fluid Flow and Transfer Processes