Computers and Operations Research
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
Genetic algorithms for flowshop scheduling problems
Computers and Industrial Engineering
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Journal of Global Optimization
Diversity-Guided Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion
Computers and Operations Research
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
An efficient stochastic hybrid heuristic for flowshop scheduling
Engineering Applications of Artificial Intelligence
Genetic algorithms, path relinking, and the flowshop sequencing problem
Evolutionary Computation
Computers and Operations Research
An alternate two phases particle swarm optimization algorithm for flow shop scheduling problem
Expert Systems with Applications: An International Journal
Computers and Operations Research
Mathematics and Computers in Simulation
The circular discrete particle swarm optimization algorithm for flow shop scheduling problem
Expert Systems with Applications: An International Journal
A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem
Information Sciences: an International Journal
A hybrid quantum-inspired genetic algorithm for flow shop scheduling
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Differential lévy-flights bat algorithm for minimization makespan in permutation flow shops
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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The permutation flow shop problem (PFSSP) is an NP-hard problem of wide engineering and theoretical background. In this paper, a differential evolution (DE) based memetic algorithm, named ODDE, is proposed for PFSSP. First, to make DE suitable for PFSSP, a new LRV rule based on random key is introduced to convert the continuous position in DE to the discrete job permutation. Second, the NEH heuristic was combined the random initialization to the population with certain quality and diversity. Third, to improve the global optimization property of DE, a DE approach based on measure of population's diversity is proposed to tuning the crossover rate. Fourth, to improve the convergence rate of DE, the opposition-based DE employs opposition-based learning for the initialization and for generation jumping to enhance the global optimal solution. Fifth, the fast local search is used for enhancing the individuals with a certain probability. Sixth, the pairwise based local search is used to enhance the global optimal solution and help the algorithm to escape from local minimum. Additionally, simulations and comparisons based on PFSSP benchmarks are carried out, which show that our algorithm is both effective and efficient. We have also evaluated our algorithm with the well known DMU problems. For the problems with the objective of minimizing makespan, the algorithm ODDE obtains 24 new upper bounds of the 40 instances, and for the problems with the objective of maximum lateness, ODDE obtains 137 new upper bounds of the 160 instances. These new upper bounds can be used for future algorithms to compare their results with ours.