A genetic algorithm for family and job scheduling in a flowline-based manufacturing cell
ICC&IE-94 Selected papers from the 16th annual conference on Computers and industrial engineering
Group scheduling on two cells with intercell movement
Computers and Operations Research
Evaluation of alternate routing policies in scheduling a job-shop type FMS
Computers and Industrial Engineering
Holonic manufacturing scheduling: architecture, cooperation mechanism and implementation
Computers in Industry - Special issue on manufacturing systems
Wasp-like Agents for Distributed Factory Coordination
Autonomous Agents and Multi-Agent Systems
Genetic algorithms in agent-based manufacturing scheduling systems
Integrated Computer-Aided Engineering
Computers and Operations Research
Computers and Industrial Engineering
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
A genetic algorithm based heuristic for scheduling of virtual manufacturing cells (VMCs)
Computers and Operations Research
Expert Systems with Applications: An International Journal
Bi-objective group scheduling in hybrid flexible flowshop: A multi-phase approach
Expert Systems with Applications: An International Journal
Job shop scheduling by pheromone approach in a dynamic environment
International Journal of Computer Integrated Manufacturing
Computers and Industrial Engineering
Scheduling groups of jobs in the two-machine flow shop
Mathematical and Computer Modelling: An International Journal
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Aiming at the problem of scheduling with flexible processing routes and exceptional parts that need to visit machines located in multiple job shop cells, a pheromone based approach (PBA) using multi-agent is presented in this paper, in which various types of pheromone inspired by ant colony optimization (ACO) are adopted as the basis of negotiation among agents. By removing redundant routes and constructing coalition agents, communication cost and negotiation complexity are reduced, and more importantly, the global performance of scheduling is improved. The performance of the PBA is evaluated via experiments with respect to the mean flow time, maximum completion time, mean tardiness, ratio of tardy parts, and ratio of intercell moves. Computational results show that compared with various heuristics, the PBA has significant advantages with respect to the performance measures considered in this paper.