Conference Proceeding Article
With the advent of e-commerce, logistics providers are faced with the challenge of handling fluctuating and sparsely distributed demand, which raises their operational costs significantly. As a result, horizontal cooperation are gaining momentum around the world. One of the major impediments, however, is the lack of stable and fair profit sharing mechanism. In this paper, we address this problem using the framework of computational cooperative games. We first present cooperative vehicle routing game as a model for collaborative logistics operations. Using the axioms of Shapley value as the conditions for fairness, we show that a stable, fair and budget balanced allocation does not exist in many instances of the game. By relaxing budget balance, we then propose an allocation scheme based on the normalized Shapley value. We show that this scheme maintains stability and fairness while requiring minimum subsidy. Finally, using numerical experiments we demonstrate the feasibility of the scheme under various settings.
Artificial Intelligence and Robotics | Operations and Supply Chain Management
Intelligent Systems and Decision Analytics
Proceedings fo the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16): February 12-17, 2016, Phoenix, Arizona
City or Country
Palo Alto, CA
AGUSSURJA, Lucas; LAU, Hoong Chuin; and CHENG, Shih-Fen.
Achieving stable and fair profit allocation with minimum subsidy in collaborative logistics. (2016). Proceedings fo the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16): February 12-17, 2016, Phoenix, Arizona. 3785-3792. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3343
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