Translated Title
Self-adaptive Negotiation Method Based on Multi-Agent Supply Chain Collaboration
Translated Abstract
Conflicts like price, amount and delivery time often appear during collaboration of manufacture supply chain, if not eliminated in time, it will affect the whole interest of supply chain. To effectively resolve the conflict of supply chain collaboration and make up for shortcomings of traditional negotiation, this paper proposes a self-adaptive negotiation method based on multi-Agent. This method takes the order of two-echelon supply chain, manufacturer and supplier, as the research object, the multi-Agent supply chain collaboration as constraint condition and the case-based reasoning as the main negotiation algorithm. Gray correlation degree is introduced into the calculation process of similarity for case set and target case. Genetic algorithm is used to optimize the weights of similar case issues. A numerical example is designed to prove this method makes the calculation of case similarity simplified which improves the efficiency of conflict resolution, and strengthens the self-adaptability which provides optimal decision for conflict resolution.
Translated Keyword
genetic algorithm
self-adaptive negotiation method
supply chain collaboration
multi-Agent
case-based reasoning
gray correlation degree
Access Number
WF:perioarticaljsjgc201403039
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