Constraint-based winner determination for auction-based scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Reducing the probability of bankruptcy through supply chain coordination
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Petri-net integration - An approach to support multi-agent process mining
Expert Systems with Applications: An International Journal
Applications of agent-based models for optimization problems: A literature review
Expert Systems with Applications: An International Journal
A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach
Engineering Applications of Artificial Intelligence
Schema and solutions for decentralised multi-project scheduling problem
International Journal of Computer Applications in Technology
A holonic approach to flexible flow shop scheduling under stochastic processing times
Computers and Operations Research
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This paper considers a supply chain that comprises multiple independent and autonomous enterprises (project managers) that seek and select various contractors to complete operations of their project. Both the project managers and contractors jointly determine the schedules of their operations while no single enterprise has complete information of other enterprises. The centralized scheduling approach that can usually obtain good global performance but must share nearly complete information that is difficult or even impractical due to the distributed nature of real-life supply chains. This paper proposes an agent-based supply chain model to support distributed scheduling. A modified contract-net protocol (MCNP) is proposed to enable more information sharing among the enterprises than conventional CNP. Experimental simulation studies are conducted to compare and contrast the performances of the centralized [centralized heuristic (CTR)], conventional CNP, and MNCP approaches. The results show that MCNP outperforms CNP and performs comparably with CTR when project complexity is high in terms of the total supply chain operating cost. Moreover, it is found that although CTR is better than MCNP in terms of global performance, MCNP yields good schedule stability when facing unexpected disturbances