Paper Info
Title
An agent-based fuzzy constraint-directed negotiation model for solving supply chain planning and scheduling problems.
Abstract
Display Omitted A set of fuzzy constraint satisfaction problems associated with supply chain planning and scheduling problem.This work proposes an agent-based fuzzy constraint-directed negotiation (AFCN).The proposed AFCN by iteratively exchanging offers/counteroffers with limited information sharing.AFCN model is sufficiently flexible to incorporate three negotiation strategies including competitive, win-win, and collaborative strategies. Supply chain planning and scheduling problems require manufacturers (project managers) to determine product configurations, select suppliers (contractors) for task allocation, and schedule project tasks while considering various production constraints among manufacturers and suppliers. Most relevant studies have focused on finding an optimal solution based on complete information provided by each enterprise in a supply chain. However, the practical implementation of complete information sharing is difficult, if not impossible, because of the fully distributed nature of the supply chain process. This work proposes an agent-based fuzzy constraint-directed negotiation (AFCN) model to solve problems associated with supply chain planning and scheduling, which are modeled as a set of fuzzy constraint satisfaction problems (FCSPs) that are interlinked via inter-agent constraints. To accommodate the perspectives and interests of each enterprise in a supply chain, conflicts among FCSPs are resolved using the AFCN protocol through the iterative exchange of offers/counter-offers with limited information sharing and without privacy breaches. A proposed offer/counter-offer represents not only a set of acceptable solutions and preferences for an operational task but also the possibility of conflict in this area. For each FCSP, the incremental process of offer/counter-offer evaluation eliminates redundant and infeasible solutions. The sharing of limited non-strategic sensitive information among agents enables them to elucidate their opponents' intentions through iterative negotiations, such that the agents can reach an agreement while ensuring that the solution to a project planning and scheduling problem is satisfactory. The AFCN model is also sufficiently flexible to incorporate different negotiation strategies such as competitive, win-win, and collaborative strategies, for various production environments. Herein, a numerical study was conducted to examine the practical viability and effectiveness of the proposed AFCN model. The experimental results show that the proposed AFCN model not only can generate a schedule that is comparable to a near-optimal solution but also is time-efficient. This indicates that the proposed AFCN is a practical and effective method for solving supply chain planning and scheduling problems in fully distributed environments.
Year
DOI
Venue
2016
10.1016/j.asoc.2016.07.030
Appl. Soft Comput.
Keywords
Field
DocType
Autonomous agents,Fuzzy constraints,Negotiation,Multi-agent system,Supply chain
Autonomous agent,Mathematical optimization,Job shop scheduling,Scheduling (computing),Fuzzy logic,Multi-agent system,Project planning,Supply chain,Information sharing,Mathematics
Journal
Volume
Issue
ISSN
48
C
1568-4946
Citations 
PageRank 
References 
6
0.44
36
Authors
5
Name
Order
Citations
PageRank
Chia-Yu Hsu1332.57
Bo-Ruei Kao2273.52
Van Lam Ho3200.98
Lin Li460.44
K. Robert Lai526326.04