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Efficiently solving the thief orienteering problem with a max-min ant colony optimization approach

arXiv 2109.13103 ↗First posted 21 Sep 2021cs.NE cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 32 references that are in the map. First posted on arXiv 21 Sep 2021.

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References · 6

  1. 2016A case study of algorithm selection for the traveling thief problemcited by 7
  2. 2016Evolutionary computation for multicomponent problems: opportunities and future directionscited by 3
  3. 2017Exact Approaches for the Travelling Thief Problemcited by 3
  4. 2014Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problemscited by 1
  5. 2017A Fully Polynomial Time Approximation Scheme for Packing While Travelingcited by 1
  6. 2020Ants can orienteer a thief in their robberycited by 1

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