期刊
OPTIMIZATION LETTERS
卷 16, 期 8, 页码 2313-2331出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11590-021-01824-y
关键词
Ant colony optimization; Multi-component problems; Knapsack problem; Orienteering problem
资金
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brazil (CAPES) [001]
- Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
- Universidade Federal de Ouro Preto (UFOP)
- Universidade Federal de Vicosa (UFV)
- Australian Research Council Project [DP200102364]
- Australian Research Council [DP200102364] Funding Source: Australian Research Council
In this article, we address the Thief Orienteering Problem (ThOP) by combining swarm intelligence with a randomized packing heuristic, achieving significant improvements on almost all 432 benchmarking instances.
We tackle the thief orienteering problem (ThOP), an academic multi-component problem that combines two classical combinatorial problems, namely the Knapsack Problem and the Orienteering Problem. In the ThOP, a thief has a time limit to steal items that distributed in a given set of cities. While traveling, the thief collects items by storing them in their knapsack, which in turn reduces the travel speed. The thief has as the objective to maximize the total profit of the stolen items. In this article, we present an approach that combines swarm-intelligence with a randomized packing heuristic. Our solution approach outperforms existing works on almost all the 432 benchmarking instances, with significant improvements.
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