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Electrical Engineering and Systems Science > Systems and Control

arXiv:2109.03539 (eess)
[Submitted on 8 Sep 2021 (v1), last revised 12 Oct 2023 (this version, v2)]

Title:Cooperative Operation of the Fleet Operator and Incentive-aware Customers in an On-demand Delivery System: A Bi-level Approach

Authors:Canqi Yao, Shibo Chen, Zaiyue Yang
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Abstract:In this paper, we study the cooperative operation problem between the fleet operator and incentive-aware customers in an on-demand delivery system. Specifically, the fleet operator offers discounts on transportation costs in exchange of the delivery time flexibility of customers. In order to capture the interaction between the fleet operator and customers, a novel bi-level optimization framework is proposed. By exploiting the strong duality, and the KKT optimality condition of customer optimization problems, we can reformulate the bi-level optimization problem as a mixed integer nonlinear programming problem. Considering the inherent difficulties of MINLP, a computationally efficient algorithm, which combines the merits of Lagrangian dual decomposition and Benders decomposition, is devised to solve the resulting MINLP problem in a distributed manner. Finally, extensive numerical experiments demonstrate that the proposed cooperation scheme can decrease the delivery fees for the customers, and reduce the operation cost of the fleet operator at the same time, thus leading to a win-win situation for both sides.
Comments: Accepted for publication in IEEE Internet of Things Journal
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2109.03539 [eess.SY]
  (or arXiv:2109.03539v2 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2109.03539
Journal reference: IEEE Internet of Things Journal, 2023
Related DOI: https://doi.org/10.1109/JIOT.2023.3324047

Submission history

From: Canqi Yao [view email]
[v1] Wed, 8 Sep 2021 10:43:16 UTC (503 KB)
[v2] Thu, 12 Oct 2023 12:10:12 UTC (1,800 KB)
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