Coordination of supply chain activities: a coalition-based approach.

Companies operate in an environment increasingly demanding in terms of flexibility and reactivity. The introduction of the entities resulting from Distributed Artificial Intelligence (DAI) and Multi-Agent Systems (MAS) in the management of enterprises prove to be an interesting technology to simulate and reproduce the collaborative and adaptive behaviors of enterprises. This article models the coordination of the various collaborative parties both inside and outside a supply chain using coordination methods of MAS mainly coalition formation mechanisms. In this paper, we present our agent modeling of supply chains, and then we detail the coalition formation algorithm. Lastly, we illustrate our approach with an example chosen in the industrial domain.Distributed Artificial Intelligence (DAI); Multi-Agent System (MAS);

A Multi-Agent Method for Forming and Dynamic Restructuring of Pareto Optimal Coalitions

International audienceThe first part of this paper presents a coalition formation method for multi-agent systems which finds a Pareto optimal solution without aggregating the preferences of the agents. This protocol is adapted to problems requiring coordination by coalition formation, where it is undesirable, or not possible, to aggregate the preferences of the agents. The second part proposes an extension of this method enabling dynamic restructuring of coalitions when changes occur in the system

Algorithmes de Recherche du Gagnant dans une Négociation Combinée

National audienc

Graph Based Search Algorithms for Optimal Winner Determination in Combined Negotiation

International audienc

A Multi-Agent Model for Overlapping Negotiations

International audienceA Multi-Agent Model for Overlapping Negotiation

Iterated Algorithm for the Optimal Winner Determination In Combined Negotiations

International audienceGenerally in multi-agent negotiations, agents are asked to submit various bids and counter-bids during several iterations of a negotiation process before reaching a compromise. In case of combined negotiations, agents need to solve particularly the winner determination problem WDP to find the best combination of bids in each iteration. In this paper, we tackle the problem of searching and updating the optimal solution of the WDP while moving from one iteration to another. We propose thereby an algorithm that searches and updates this optimal solution. Our algorithm is essentially based on exploring very simple graphs for shared and unshared items. These graphs speed up optimal solution searching