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Modern heuristic techniques for combinatorial problems
A genetic algorithm for flowshop sequencing
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Job Shop Scheduling with Genetic Algorithms
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AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Are Long Path Problems Hard for Genetic Algorithms?
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
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Mutation-crossover isomorphisms and the construction of discriminating functions
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Algorithm performance and problem structure for flow-shop scheduling
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A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion
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RGFGA: An Efficient Representation and Crossover for Grouping Genetic Algorithms
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Considering scheduling and preventive maintenance in the flowshop sequencing problem
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A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
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An effective hybrid DE-based algorithm for multi-objective flow shop scheduling with limited buffers
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A Constructive Genetic Algorithm for permutation flowshop scheduling
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A particle swarm-based genetic algorithm for scheduling in an agile environment
Computers and Industrial Engineering
Parallel Path-Relinking Method for the Flow Shop Scheduling Problem
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
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A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Solving the flow shop problem by parallel programming
Journal of Parallel and Distributed Computing
A DE-based approach to no-wait flow-shop scheduling
Computers and Industrial Engineering
How the landscape of random job shop scheduling instances depends on the ratio of jobs to machines
Journal of Artificial Intelligence Research
The property analysis of evolutionary algorithms applied to spanning tree problems
Applied Intelligence
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
On a property analysis of representations for spanning tree problems
EA'05 Proceedings of the 7th international conference on Artificial Evolution
A hybrid genetic algorithm for the flow-shop scheduling problem
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Path relinking in pareto multi-objective genetic algorithms
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Grid branch-and-bound for permutation flowshop
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Solving bi-objective flow shop problem with hybrid path relinking algorithm
Applied Soft Computing
Maximizing stochastic robustness of static resource allocations in a periodic sensor driven cluster
Future Generation Computer Systems
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In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly.