A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
The ant colony optimization meta-heuristic
New ideas in optimization
A Mixed-Initiative Planning Approach to Exploratory Data Analysis
A Mixed-Initiative Planning Approach to Exploratory Data Analysis
An ant colony system for permutation flow-shop sequencing
Computers and Operations Research
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An improved particle swarm optimization algorithm for flowshop scheduling problem
Information Processing Letters
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Bi-Objective Ant Colony Optimization approach to optimize production and maintenance scheduling
Computers and Operations Research
A meta-heuristic approach to solve a JIT scheduling problem in hybrid flow shop
Engineering Applications of Artificial Intelligence
The best-so-far selection in Artificial Bee Colony algorithm
Applied Soft Computing
Computers and Operations Research
A bi-objective iterated local search heuristic with path-relinking for the p-median problem
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Advances in Engineering Software
A new ant colony algorithm for makespan minimization in permutation flow shops
Computers and Industrial Engineering
Multi-objective optimization with fuzzy measures and its application to flow-shop scheduling
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Scheduling Cellular Manufacturing Systems Using ACO and GA
International Journal of Applied Metaheuristic Computing
Artificial bee colony algorithm: a survey
International Journal of Advanced Intelligence Paradigms
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Flow shop scheduling problem consists of scheduling given jobs with same order at all machines. The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, multi-objective approach for scheduling to reduce the total scheduling cost is important. Hence, in this study, we consider the flow shop scheduling problem with multi-objectives of makespan, total flow time and total machine idle time. Ant colony optimization (ACO) algorithm is proposed to solve this problem which is known as NP-hard type. The proposed algorithm is compared with solution performance obtained by the existing multi-objective heuristics. As a result, computational results show that proposed algorithm is more effective and better than other methods compared.