Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The delivery man problem and cumulative matroids
Operations Research
Total flowtime in no-wait flowshops with separated setup times
Computers and Operations Research
P-Complete Approximation Problems
Journal of the ACM (JACM)
Ant algorithms for discrete optimization
Artificial Life
A new heuristic and dominance relations for no-wait flowshops with setups
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Expert Systems with Applications: An International Journal
An efficient simple metaheuristic for minimizing the makespan in two-machine no-wait job shops
Computers and Operations Research
Robotics and Computer-Integrated Manufacturing
Computers and Industrial Engineering
International Journal of Computer Mathematics
Integrated process planning and scheduling by an agent-based ant colony optimization
Computers and Industrial Engineering
An island model for the no-wait flow shop scheduling problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Engineering Applications of Artificial Intelligence
Computers and Operations Research
Information Sciences: an International Journal
A modified ant colony system for solving the travelling salesman problem with time windows
Mathematical and Computer Modelling: An International Journal
Multi-objective no-wait hybrid flowshop scheduling problem with transportation times
International Journal of Computational Science and Engineering
A new evolutionary clustering search for a no-wait flow shop problem with set-up times
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
A multi-objective ant colony system algorithm for virtual machine placement in cloud computing
Journal of Computer and System Sciences
Expert Systems with Applications: An International Journal
Journal of Intelligent Manufacturing
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Ant colony optimization (ACO) is a meta-heuristic proposed to derive approximate solutions for computationally hard problems by emulating the natural behaviors of ants. In the literature, several successful applications have been reported for graph-based optimization problems, such as vehicle routing problems and traveling salesman problems. In this paper, we propose an application of the ACO to a two-machine flowshop scheduling problem. In the flowshop, no intermediate storage is available between two machines and each operation demands a setup time on the machines. The problem seeks to compose a schedule that minimizes the total completion time. We first present a transformation of the scheduling problem into a graph-based model. An ACO algorithm is then developed with several specific features incorporated. A series of computational experiments is conducted by comparing our algorithm with previous heuristic algorithms. Numerical results evince that the ACO algorithm exhibits impressive performances with small error ratios. The results in the meantime demonstrate the success of ACO's applications to the scheduling problem of interest.