Simulated annealing: theory and applications
Simulated annealing: theory and applications
Computers and Operations Research
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms for flowshop scheduling problems
Computers and Industrial Engineering
One-operator–two-machine flowshop scheduling with setup and dismounting times
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Scheduling parallel machines with a single server: some solvable cases and heuristics
Computers and Operations Research
Genetic algorithms, path relinking, and the flowshop sequencing problem
Evolutionary Computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Minimizing total flow time in permutation flow shop scheduling with improved simulated annealing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
International Journal of Bio-Inspired Computation
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Scheduling models that allow the handling of pre-operational setup have been a source of major interests because of their practical relevance and theoretical impacts. Two-stage flow-lines have drawn much attention to researchers as they are simple, yet practical and can be easily extended to represent more complex situations. In this paper, two-machine flow-shop problems with a single setup server are surveyed. These problems have been shown to be NP-complete with special cases that are polynomial-time solvable. Several heuristics are proposed to solve the problems in general case, including simulated annealing, Tabu search, genetic algorithms, GRASP, and other hybrids. The results on small inputs are compared with the optimal solutions and results on large inputs are compared to a lower bound. Experiments show that the heuristics developed, obtain nearly optimal solutions.