Minimizing the sum of the job completion times in the two-machine flow shop by Lagrangian relaxation
Annals of Operations Research
An effective heuristic for flow shop problems with total flow time as criterion
Proceedings of the 15th annual conference on Computers and industrial engineering
Flowshop scheduling with dominant machines
Computers and Operations Research
A heuristic algorithm for mean flowtime objective in flowshop scheduling
Computers and Operations Research
Swarm intelligence
Reaction-Diffusion Model of a Honeybee Colony's Foraging Behaviour
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Comparison of heuristics for flowtime minimisation in permutation flowshops
Computers and Operations Research
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
A combinatorial particle swarm optimisation for solving permutation flowshop problems
Computers and Industrial Engineering
An energy-efficient real-time scheduling scheme on dual-channel networks
Information Sciences: an International Journal
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Computers and Industrial Engineering
Computers and Operations Research
Computers and Operations Research
Computers and Operations Research
Some scheduling problems with general position-dependent and time-dependent learning effects
Information Sciences: an International Journal
Single-machine scheduling with sum-of-logarithm-processing-times-based learning considerations
Information Sciences: an International Journal
Some single-machine and m-machine flowshop scheduling problems with learning considerations
Information Sciences: an International Journal
A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem
Information Sciences: an International Journal
Engineering optimizations via nature-inspired virtual bee algorithms
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
A modified Artificial Bee Colony algorithm for real-parameter optimization
Information Sciences: an International Journal
A chaotic digital secure communication based on a modified gravitational search algorithm filter
Information Sciences: an International Journal
A hybrid artificial bee colony algorithm for graph 3-coloring
SIDE'12 Proceedings of the 2012 international conference on Swarm and Evolutionary Computation
A discrete artificial bee colony algorithm for the multi-objective redistricting problem
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Hybridizing VNS and path-relinking on a particle swarm framework to minimize total flowtime
Expert Systems with Applications: An International Journal
Computers and Operations Research
Information Sciences: an International Journal
Optimization of cutting parameters in multi-pass turning using artificial bee colony-based approach
Information Sciences: an International Journal
An artificial bee colony algorithm for the maximally diverse grouping problem
Information Sciences: an International Journal
Artificial bee colony algorithm: a survey
International Journal of Advanced Intelligence Paradigms
A novel artificial bee colony algorithm with Powell's method
Applied Soft Computing
A hybrid metaheuristic for the cyclic antibandwidth problem
Knowledge-Based Systems
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Obtaining an optimal solution for a permutation flowshop scheduling problem with the total flowtime criterion in a reasonable computational timeframe using traditional approaches and optimization tools has been a challenge. This paper presents a discrete artificial bee colony algorithm hybridized with a variant of iterated greedy algorithms to find the permutation that gives the smallest total flowtime. Iterated greedy algorithms are comprised of local search procedures based on insertion and swap neighborhood structures. In the same context, we also consider a discrete differential evolution algorithm from our previous work. The performance of the proposed algorithms is tested on the well-known benchmark suite of Taillard. The highly effective performance of the discrete artificial bee colony and hybrid differential evolution algorithms is compared against the best performing algorithms from the existing literature in terms of both solution quality and CPU times. Ultimately, 44 out of the 90 best known solutions provided very recently by the best performing estimation of distribution and genetic local search algorithms are further improved by the proposed algorithms with short-term searches. The solutions known to be the best to date are reported for the benchmark suite of Taillard with long-term searches, as well.