A revolution: belief propagation in graphs with cycles
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Combinatorial auctions for supply chain formation
Proceedings of the 2nd ACM conference on Electronic commerce
Agent-based negotiation and decision making for dynamic supply chain formation
Engineering Applications of Artificial Intelligence
Decentralized supply chain formation: a market protocol and competitive equilibrium analysis
Journal of Artificial Intelligence Research
Scalable decentralized supply chain formation through binarized belief propagation
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
CHAINME: fast decentralized finding of better supply chains
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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Decentralised supply chain formation involves determining the set of producers within a network able to supply goods to one or more consumers at the lowest cost. This problem is frequently tackled using auctions and negotiations. In this paper we show how it can be cast as an optimisation of a pairwise cost function. Optimising this class of functions is NP-hard but good approximations to the global minimum can be obtained using Loopy Belief Propagation (LBP). Here we detail a LBP-based approach to the supply chain formation problem, involving decentralised message-passing between potential participants. Our approach is evaluated against a well-known double-auction method and an optimal centralised technique, showing several improvements: it obtains better solutions for most networks that admit a competitive equilibrium Competitive equilibrium as defined in [3] is used as a means of classifying results on certain networks to allow for minor inefficiencies in their auction protocol and agent bidding strategies. while also solving problems where no competitive equilibrium exists, for which the double-auction method frequently produces inefficient solutions.