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Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers

Author

Listed:
  • Yezekael Hayel

    (LIA/CERI)

  • Dominique Quadri

    (LRI)

  • Tania Jiménez

    (LIA/CERI)

  • Luce Brotcorne

    (INRIA)

Abstract

The goal of this paper is to introduce bounded rational behaviors in a competitive queuing system. Furthermore, we propose a realistic queuing model for two last-mile delivery services in which consumers are in competition. This work is derived from a real-world e-commerce application. We study the problem using a game theoretical point of view: the e-consumers are interacting through the last-mile delivery service system creating congestion for each other. Specifically, we focus our analysis on several equilibrium concepts from congestion/routing games: Wardrop and Logit equilibria. The difference in these equilibrium concepts is on the rationality level of players in the game. We are able to prove the existence and uniqueness of both equilibria. We compare them through a new metric called the Price of Rationality and we also compare each one to the social optimum solution through the Price of Anarchy. Some numerical results are presented in order to illustrate the theoretical results obtained.

Suggested Citation

  • Yezekael Hayel & Dominique Quadri & Tania Jiménez & Luce Brotcorne, 2016. "Decentralized optimization of last-mile delivery services with non-cooperative bounded rational customers," Annals of Operations Research, Springer, vol. 239(2), pages 451-469, April.
    • Handle: RePEc:spr:annopr:v:239:y:2016:i:2:d:10.1007_s10479-014-1647-x
    DOI: 10.1007/s10479-014-1647-x
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    References listed on IDEAS

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    1. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    2. Agatz, Niels A.H. & Fleischmann, Moritz & van Nunen, Jo A.E.E., 2008. "E-fulfillment and multi-channel distribution - A review," European Journal of Operational Research, Elsevier, vol. 187(2), pages 339-356, June.
    3. Simon P. Anderson & Jacob K. Goeree & Charles A. Holt, 2002. "The Logit Equilibrium: A Perspective on Intuitive Behavioral Anomalies," Southern Economic Journal, John Wiley & Sons, vol. 69(1), pages 21-47, July.
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    Cited by:

    1. Ghosh, Souvik & Hassin, Refael, 2021. "Inefficiency in stochastic queueing systems with strategic customers," European Journal of Operational Research, Elsevier, vol. 295(1), pages 1-11.
    2. Juan Guillermo Urzúa-Morales & Juan Pedro Sepulveda-Rojas & Miguel Alfaro & Guillermo Fuertes & Rodrigo Ternero & Manuel Vargas, 2020. "Logistic Modeling of the Last Mile: Case Study Santiago, Chile," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    3. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    4. Tang, Yuk Ming & Chau, Ka Yin & Xu, Duo & Liu, Xiaoyun, 2021. "Consumer perceptions to support IoT based smart parcel locker logistics in China," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    5. Zhang, Wenwei & Xu, Min & Wang, Shuaian, 2023. "Joint location and pricing optimization of self-service in urban logistics considering customers’ choice behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    6. Lin Zhou & Xu Wang & Lin Ni & Yun Lin, 2016. "Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    7. Zhuo Sun & Ni Yan & Yining Sun & Haobin Li, 2019. "Location-Routing Optimization with Split Demand for Customer Self-Pickup via Data Analysis and Heuristics Search," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-24, December.
    8. Chen Wei & Sobhan Asian & Gurdal Ertek & Zhi-Hua Hu, 2020. "Location-based pricing and channel selection in a supply chain: a case study from the food retail industry," Annals of Operations Research, Springer, vol. 291(1), pages 959-984, August.
    9. Li, Qiaoru & Wang, Yuanyuan & Li, Kun & Chen, Liang & Wei, Zhenlin, 2019. "Evolutionary dynamics of the last mile travel choice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    10. Yandong He & Xu Wang & Yun Lin & Fuli Zhou, 2016. "Optimal Partner Combination for Joint Distribution Alliance using Integrated Fuzzy EW-AHP and TOPSIS for Online Shopping," Sustainability, MDPI, vol. 8(4), pages 1-18, April.

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