Single facility multi-class job scheduling
Computers and Operations Research
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Heuristics for operator scheduling in group technology cells
Computers and Operations Research
Group scheduling on two cells with intercell movement
Computers and Operations Research
Two-machine flowshop group scheduling problem
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion
Computers and Operations Research
Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing
Two-machine group scheduling problems in discrete parts manufacturing with sequence-dependent setups
Computers and Operations Research
Forming part families by using genetic algorithm and designing machine cells under demand changes
Computers and Operations Research
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Expert Systems with Applications: An International Journal
Computers and Operations Research
Computers and Industrial Engineering
Minimizing makespan in a flow-line manufacturing cell with sequence dependent family setup times
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Scheduling Cellular Manufacturing Systems Using ACO and GA
International Journal of Applied Metaheuristic Computing
Robotics and Computer-Integrated Manufacturing
Dynamic parts scheduling in multiple job shop cells considering intercell moves and flexible routes
Computers and Operations Research
Effect of solution representations on Tabu search in scheduling applications
Computers and Operations Research
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The broad applications of cellular manufacturing make flowline manufacturing cell scheduling problems with sequence dependent family setup times a core topic in the field of scheduling. Due to computational complexity, almost all published studies focus on using permutation schedules to deal with this problem. To explore the potential effectiveness of treating this argument using non-permutation schedules, three prominent types of metaheuristics-a simulated annealing, a genetic algorithm and a tabu search-are proposed and empirically evaluated. The experimental results demonstrate that in general, the improvement made by non-permutation schedules over permutation schedules for the due-date-based performance criteria were significantly better than that for the completion-time-based criteria. The results of this study will provide practitioners a guideline as to when to adopt a non-permutation schedule, which may exhibit better performance with additional computational efforts.