Routing and scheduling in a flexible job shop by tabu search
Annals of Operations Research - Special issue on Tabu search
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
Computers and Operations Research
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
Robotics and Computer-Integrated Manufacturing
Computers and Industrial Engineering
Computers and Industrial Engineering
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Applying the clonal selection principle to find flexible job-shop schedules
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Assignment and Scheduling in Flexible Job-Shops by Hierarchical Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A hybrid harmony search algorithm for the flexible job shop scheduling problem
Applied Soft Computing
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The classical job shop scheduling problem (JSP) is the most popular machine scheduling model in practice and is well known as NP-hard. The formulation of the JSP is based on the assumption that for each part type or job there is only one process plan that prescribes the sequence of operations and the machine on which each operation has to be performed. Flexible job shop scheduling problem (FJSP) is an extension of the JSP, which allows an operation to be processed by any machine from a given set. Since FJSP requires an additional decision of machine allocation during scheduling, therefore it is much more complex problem than JSP. To solve such NP-hard problems, heuristic approaches are commonly preferred over the traditional mathematical techniques. This paper proposes a particle swarm optimization (PSO) based heuristic for solving the FJSP for minimum makespan time criterion. The performance of the proposed PSO is evaluated by comparing its results with the results obtained using ILOG Solver, a constraint-programming tool. The comparison of the results proves the effectiveness of the proposed PSO for solving FJSP instances.