Decentralized supply chain formation using max-sum loopy belief propagation

Abstract

Supply chain formation is the process by which a set of producers within a network determine the subset of these producers able to form a chain to supply goods to one or more consumers at the lowest cost. This problem has been tackled in a number of ways, including auctions, negotiations, and argumentation-based approaches. In this paper we show how this problem can be cast as an optimization of a pairwise cost function. Optimizing this class of energy functions is NP-hard but efficient approximations to the global minimum can be obtained using loopy belief propagation (LBP). Here we detail a max-sum LBP-based approach to the supply chain formation problem, involving decentralized message-passing between supply chain participants. Our approach is evaluated against a well-known decentralized double-auction method and an optimal centralized technique, showing several improvements on the auction method: it obtains better solutions for most network instances which allow for competitive equilibrium (Competitive equilibrium in Walsh and Wellman is a set of producer costs which permits a Pareto optimal state in which agents in the allocation receive non-negative surplus and agents not in the allocation would acquire non-positive surplus by participating in the supply chain) while also optimally solving problems where no competitive equilibrium exists, for which the double-auction method frequently produces inefficient solutions. © 2012 Wiley Periodicals, Inc.

Publication DOI: https://doi.org/10.1111/j.1467-8640.2012.00446.x
Divisions: ?? 50811700Jl ??
Additional Information: Winsper, M. , & Chli, M. (2012). Decentralized supply chain formation using max-sum loopy belief propagation. Computational intelligence, 29(2), which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8640.2012.00446.x/abstract
Uncontrolled Keywords: loopy belief propagation,max-sum algorithm,supply chain formation,Artificial Intelligence,Computational Mathematics
Publication ISSN: 1467-8640
Last Modified: 16 Jan 2024 18:08
Date Deposited: 22 Jul 2013 14:45
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://onlineli ... 0446.x/abstract (Publisher URL)
PURE Output Type: Article
Published Date: 2013-05
Published Online Date: 2012-07-04
Authors: Winsper, Michael
Chli, Maria (ORCID Profile 0000-0002-2840-4475)

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