An agent-based model to support multi-issue negotiation in green supply chain

Abstract

To implement green supply chain, a company has to consider sustainability impacts in assessing potential suppliers. Thereby, the supplier evaluation and selection criteria would include various key performance indicators such as price, quality, delivery, as well as environmental and corporate social responsibility aspects. Researchers have proposed numerous multi-criteria decision making (MCDM) approaches for evaluating the multiple conflicting criteria in supplier selection. However, most of the existing approaches have ignored some important issues in business environment such as supplier qualification, supplier autonomy, negotiation between manufacturer and supplier, etc.

In this thesis, a multi-agent system (MAS) is proposed for supplier selection in green supply chain. It comprises two types of autonomous agents, namely, buyer agent and seller agents, to represent the interests of manufacturer and suppliers, respectively.

The proposed MAS presents three prominent features. First, the proposed supplier selection criteria incorporate the conventional, environmental and social aspects in the supplier selection process. The criteria are classified into negotiable and non-negotiable criteria. Initially, all criteria are included to evaluate and rank all the candidate suppliers. Subsequently, the top-ranked candidates are invited to participate in the bargaining process. In this regard, the negotiable criteria are used for assessing the quality of an offer, while the non-negotiable criteria, i.e. environmental and social criteria, influence the manufacturer’s negotiation attitude to candidate suppliers. The classification enables the manufacturer to fully utilize the performance values of all criteria.

Secondly, supplier selection is implemented in a two-stage methodology. The TOPSIS method is devised in the first stage to shortlist some suitable candidate suppliers for entering negotiation in the next stage. In the second stage, the agent-based negotiation process is adopted for selecting the final supplier. Representing the manufacturer and the shortlisted suppliers respectively, the buyer and seller agents bargain on a number of negotiable issues in the multi-round negotiation. A multi-issue and multilateral agent interaction protocol, which is an extension of the contract net protocol, is implemented in the MAS. Accordingly, the buyer agent coordinates with the seller agents to exchange offers and counteroffers.

Thirdly, a novel preference-based negotiation strategy is used to govern the behavior of agents during negotiation. A heuristics model with the Particle Swarm Optimization (PSO) algorithm and Adaptive Penalty Function has been designed and implemented to realize the proposed negotiation strategy. The strategy guides the autonomous agents to narrow down the discrepancies in the values of the negotiable criteria (price, delivery days, contract length) in their offers, and simultaneously search a mutually beneficial and acceptable agreement. The negotiation payoffs and negotiation time are improved.

Experimental results indicate that the proposed agent-based model could help the manufacturer to identify the most appropriate supplier and improve the quality of final agreement. In addition, the model successfully integrates supplier qualification and automated negotiation, and promotes supplier autonomy in the supplier selection process.