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
A heuristic algorithm for mean flowtime objective in flowshop scheduling
Computers and Operations Research
New heuristics for no-wait flowshops to minimize makespan
Computers and Operations Research
A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion
Computers and Operations Research
Comparison of heuristics for flowtime minimisation in permutation flowshops
Computers and Operations Research
Differential evolution for sequencing and scheduling optimization
Journal of Heuristics
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Genetic algorithms, path relinking, and the flowshop sequencing problem
Evolutionary Computation
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
A self-guided genetic algorithm for flowshop scheduling problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Differential evolution algorithms for the generalized assignment problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Information Sciences: an International Journal
Estimation of distribution algorithm for permutation flow shops with total flowtime minimization
Computers and Industrial Engineering
Brief paper: An improved differential evolution algorithm for the task assignment problem
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
A Self-guided Genetic Algorithm for permutation flowshop scheduling problems
Computers and Operations Research
Solving the stochastic dynamic lot-sizing problem through nature-inspired heuristics
Computers and Operations Research
Computers and Operations Research
Extended artificial chromosomes genetic algorithm for permutation flowshop scheduling problems
Computers and Industrial Engineering
Minimizing the total flowtime flowshop with blocking using a discrete artificial bee colony
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Hybridizing VNS and path-relinking on a particle swarm framework to minimize total flowtime
Expert Systems with Applications: An International Journal
A differential evolution approach for NTJ-NFSSP with SDSTs and RDs
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Information Sciences: an International Journal
Memetic differential evolution for vehicle routing problem with time windows
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Computers and Operations Research
Computers and Operations Research
Swarm optimisation algorithms applied to large balanced communication networks
Journal of Network and Computer Applications
Computers and Operations Research
A real-integer-discrete-coded differential evolution
Applied Soft Computing
On insertion tie-breaking rules in heuristics for the permutation flowshop scheduling problem
Computers and Operations Research
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Very recently, Pan et al. [Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, GECCO07, pp. 126-33] presented a new and novel discrete differential evolution algorithm for the permutation flowshop scheduling problem with the makespan criterion. On the other hand, the iterated greedy algorithm is proposed by [Ruiz, R., & Stutzle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-49] for the permutation flowshop scheduling problem with the makespan criterion. However, both algorithms are not applied to the permutation flowshop scheduling problem with the total flowtime criterion. Based on their excellent performance with the makespan criterion, we extend both algorithms in this paper to the total flowtime objective. Furthermore, we propose a new and novel referenced local search procedure hybridized with both algorithms to further improve the solution quality. The referenced local search exploits the space based on reference positions taken from a reference solution in the hope of finding better positions for jobs when performing insertion operation. Computational results show that both algorithms with the referenced local search are either better or highly competitive to all the existing approaches in the literature for both objectives of makespan and total flowtime. Especially for the total flowtime criterion, their performance is superior to the particle swarm optimization algorithms proposed by [Tasgetiren, M. F., Liang, Y. -C., Sevkli, M., Gencyilmaz, G. (2007). Particle swarm optimization algorithm for makespan and total flowtime minimization in permutation flowshop sequencing problem. European Journal of Operational Research, 177(3), 1930-47] and [Jarboui, B., Ibrahim, S., Siarry, P., Rebai, A. (2007). A combinatorial particle swarm optimisation for solving permutation flowshop problems. Computers &Industrial Engineering, doi:10.1016/j.cie.2007.09.006]. Ultimately, for Taillard's benchmark suite, four best known solutions for the makespan criterion as well as 40 out of the 90 best known solutions for the total flowtime criterion are further improved by either one of the algorithms presented in this paper.