A non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorChagas, Jonatas Batista Costa das-
Autor(es): dc.creatorBlank, Julian-
Autor(es): dc.creatorWagner, Markus-
Autor(es): dc.creatorSouza, Marcone Jamilson Freitas-
Autor(es): dc.creatorDeb, Kalyanmoy-
Data de aceite: dc.date.accessioned2025-08-21T15:42:21Z-
Data de disponibilização: dc.date.available2025-08-21T15:42:21Z-
Data de envio: dc.date.issued2022-02-09-
Data de envio: dc.date.issued2022-02-09-
Data de envio: dc.date.issued2019-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/14476-
Fonte completa do material: dc.identifierhttps://link.springer.com/article/10.1007/s10732-020-09457-7-
Fonte completa do material: dc.identifierhttps://doi.org/10.1007/s10732-020-09457-7-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1022077-
Descrição: dc.descriptionIn this paper, we propose a method to solve a bi-objective variant of the well-studied traveling thief problem (TTP). The TTP is a multi-component problem that combines two classic combinatorial problems: traveling salesman problem and knapsack problem. We address the BI-TTP, a bi-objective version of the TTP, where the goal is to minimize the overall traveling time and to maximize the profit of the collected items. Our proposed method is based on a biased-random key genetic algorithm with customizations addressing problem-specific characteristics. We incorporate domain knowledge through a combination of near-optimal solutions of each subproblem in the initial population and use a custom repair operator to avoid the evaluation of infeasible solutions. The bi-objective aspect of the problem is addressed through an elite population extracted based on the non-dominated rank and crowding distance. Furthermore, we provide a comprehensive study showing the influence of each parameter on the performance. Finally, we discuss the results of the BI-TTP competitions at EMO-2019 and GECCO-2019 conferences where our method has won first and second places, respectively, thus proving its ability to find high-quality solutions consistently.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectCombinatorial optimization-
Palavras-chave: dc.subjectMulti-objective optimization-
Palavras-chave: dc.subjectReal-world optimization problem-
Título: dc.titleA non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem.-
Aparece nas coleções:Repositório Institucional - UFOP

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