Bidding-based process planning and scheduling in a multi-agent system
Computers and Industrial Engineering
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
A simulated annealing-based optimization approach for integrated process planning and scheduling
International Journal of Computer Integrated Manufacturing
Applications of particle swarm optimisation in integrated process planning and scheduling
Robotics and Computer-Integrated Manufacturing
Integrated process planning and scheduling by an agent-based ant colony optimization
Computers and Industrial Engineering
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Integrated process planning and scheduling (IPPS) is an NP-hard problem, the major research on the multi-agent system (MAS) based IPPS systems has focused on the establishment of negotiation protocols to accomplish the integration of process planning and scheduling. However, not much consideration has been paid to the dynamic factors of current manufacturing systems. In this paper, an MAS architecture is proposed to solve the dynamic IPPS problem with embedded heuristic algorithms. The proposed MAS system can be combined with a variety of heuristic methods to support dynamic process planning, scheduling and re-scheduling. As a result, the proposed MAS system for dynamic IPPS using heuristics possesses high flexibility, extensibility, and accessibility for manufacturing applications.