The shifting bottleneck procedure for job shop scheduling
Management Science
An algorithm for solving the job-shop problem
Management Science
Genetic algorithms and job shop scheduling
Proceedings of the 12th annual conference on Computers and industrial engineering
Job shop scheduling by simulated annealing
Operations Research
Applying tabu search to the job-shop scheduling problem
Annals of Operations Research - Special issue on Tabu search
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Flexible scheduling in a machining center through genetic algorithms
Computers and Industrial Engineering
Multi-objective genetic algorithm and its applications to flowshop scheduling
Computers and Industrial Engineering
Automation, Production Systems and Computer-Aided Manufacturing
Automation, Production Systems and Computer-Aided Manufacturing
Tabu Search
Filtered-beam-search-based algorithm for dynamic rescheduling in FMS
Robotics and Computer-Integrated Manufacturing
Computers & Mathematics with Applications
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The performance of a scheduling system, in practice, is not evaluated to satisfy a single objective, but to obtain a trade-off schedule regarding multiple objectives. Therefore, in this research, we make use of one of the multiple objective decision-making methods, a global criterion approach, to develop a multi-objective model for solving FMS scheduling problems with consideration of three performance measures, namely minimum mean job flow time, mean job tardiness, and minimum mean machine idle time, simultaneously. In addition, hybrid heuristics, which are a combination of two common local search methods, simulated annealing and tabu search, are also proposed for solving the addressed FMS scheduling problems. The feasibility and adaptability of the proposed heuristics are investigated through experimental results.