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A memetic algorithm for the multiperiod vehicle routing problem with profit

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  • Zhang, Zizhen
  • Che, Oscar
  • Cheang, Brenda
  • Lim, Andrew
  • Qin, Hu

Abstract

In this paper, we extend upon current research in the vehicle routing problem whereby labour regulations affect planning horizons, and therefore, profitability. We call this extension the multiperiod vehicle routing problem with profit (mVRPP). The goal is to determine routes for a set of vehicles that maximizes profitability from visited locations, based on the conditions that vehicles can only travel during stipulated working hours within each period in a given planning horizon and that the vehicles are only required to return to the depot at the end of the last period. We propose an effective memetic algorithm with a giant-tour representation to solve the mVRPP. To efficiently evaluate a chromosome, we develop a greedy procedure to partition a given giant-tour into individual routes, and prove that the resultant partition is optimal. We evaluate the effectiveness of our memetic algorithm with extensive experiments based on a set of modified benchmark instances. The results indicate that our approach generates high-quality solutions that are reasonably close to the best known solutions or proven optima, and significantly better than the solutions obtained using heuristics employed by professional schedulers.

Suggested Citation

  • Zhang, Zizhen & Che, Oscar & Cheang, Brenda & Lim, Andrew & Qin, Hu, 2013. "A memetic algorithm for the multiperiod vehicle routing problem with profit," European Journal of Operational Research, Elsevier, vol. 229(3), pages 573-584.
    • Handle: RePEc:eee:ejores:v:229:y:2013:i:3:p:573-584
    DOI: 10.1016/j.ejor.2012.11.059
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    Cited by:

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    2. Aksen, Deniz & Kaya, Onur & Sibel Salman, F. & Tüncel, Özge, 2014. "An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 413-426.
    3. Thibaut Vidal & Nelson Maculan & Luiz Satoru Ochi & Puca Huachi Vaz Penna, 2016. "Large Neighborhoods with Implicit Customer Selection for Vehicle Routing Problems with Profits," Transportation Science, INFORMS, vol. 50(2), pages 720-734, May.
    4. Aderemi Oluyinka Adewumi & Olawale Joshua Adeleke, 2018. "A survey of recent advances in vehicle routing problems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 155-172, February.
    5. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    6. 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.
    7. Luo, Hao & Yang, Xuan & Kong, Xiang T.R., 2019. "A synchronized production-warehouse management solution for reengineering the online-offline integrated order fulfillment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 211-230.

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