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Pareto mimic algorithm: An approach to the team orienteering problem

Author

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  • Ke, Liangjun
  • Zhai, Laipeng
  • Li, Jing
  • Chan, Felix T.S.

Abstract

The team orienteering problem is an important variant of the vehicle routing problem. In this paper, a new algorithm, called Pareto mimic algorithm, is proposed to deal with it. This algorithm maintains a population of incumbent solutions which are updated using Pareto dominance. It uses a new operator, called mimic operator, to generate a new solution by imitating an incumbent solution. Furthermore, to improve the quality of a solution, it employs an operator, called swallow operator which attempts to swallow (or insert) an infeasible node and then repair the resulting infeasible solution. A comparative study supports the effectiveness of the proposed algorithm, especially, our algorithm can quickly find new better results for several large-scale instances. We also demonstrate that Pareto mimic algorithm can be generalized to solve other routing problems, e.g., the capacitated vehicle routing problem.

Suggested Citation

  • Ke, Liangjun & Zhai, Laipeng & Li, Jing & Chan, Felix T.S., 2016. "Pareto mimic algorithm: An approach to the team orienteering problem," Omega, Elsevier, vol. 61(C), pages 155-166.
  • Handle: RePEc:eee:jomega:v:61:y:2016:i:c:p:155-166
    DOI: 10.1016/j.omega.2015.08.003
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    References listed on IDEAS

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    Cited by:

    1. Katharina Glock & Anne Meyer, 2020. "Mission Planning for Emergency Rapid Mapping with Drones," Transportation Science, INFORMS, vol. 54(2), pages 534-560, March.
    2. Orlis, Christos & Laganá, Demetrio & Dullaert, Wout & Vigo, Daniele, 2020. "Distribution with Quality of Service Considerations: The Capacitated Routing Problem with Profits and Service Level Requirements," Omega, Elsevier, vol. 93(C).
    3. Kirac, Emre & Milburn, Ashlea Bennett, 2018. "A general framework for assessing the value of social data for disaster response logistics planning," European Journal of Operational Research, Elsevier, vol. 269(2), pages 486-500.
    4. Racha El-Hajj & Rym Nesrine Guibadj & Aziz Moukrim & Mehdi Serairi, 2020. "A PSO based algorithm with an efficient optimal split procedure for the multiperiod vehicle routing problem with profit," Annals of Operations Research, Springer, vol. 291(1), pages 281-316, August.
    5. Xia, Jun & Wang, Kai & Wang, Shuaian, 2019. "Drone scheduling to monitor vessels in emission control areas," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 174-196.
    6. Christos Orlis & Nicola Bianchessi & Roberto Roberti & Wout Dullaert, 2020. "The Team Orienteering Problem with Overlaps: An Application in Cash Logistics," Transportation Science, INFORMS, vol. 54(2), pages 470-487, March.

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