Hybrid flow shop scheduling: a survey
Computers and Industrial Engineering
Ant algorithms for discrete optimization
Artificial Life
An Ant Algorithm with a New Pheromone Evaluation Rule for Total Tardiness Problems
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Two-machine flowshop scheduling with a secondary criterion
Computers and Operations Research
An ant colony system for permutation flow-shop sequencing
Computers and Operations Research
Ant Colony Optimization
A neuro-tabu search heuristic for the flow shop scheduling problem
Computers and Operations Research
Ant colony optimization theory: a survey
Theoretical Computer Science
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Heuristic algorithms for the two-stage hybrid flowshop problem
Operations Research Letters
Journal of Intelligent Manufacturing
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We consider the problem of scheduling jobs in a hybrid flowshop with two stages. Our objective is to minimize both the makespan and the total completion time of jobs. This problem has been little studied in the literature. To solve the problem, we propose an ant colony optimization procedure. Computational experiments are conducted using random-generated instances from the literature. In comparison against other well-known heuristics from the literature, experimental results show that our algorithm outperforms such heuristics.