Future Generation Computer Systems
Advanced planning and scheduling with outsourcing in manufacturing supply chain
Computers and Industrial Engineering - Supply chain management
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
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem
INFORMS Journal on Computing
Ant Colony Optimization
Computers and Industrial Engineering
Ant Algorithms: Theory and Applications
Programming and Computing Software
Ant colony optimization theory: a survey
Theoretical Computer Science
Computers and Operations Research
Ant colony optimization for multi-objective flow shop scheduling problem
Computers and Industrial Engineering
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Scheduling Algorithms
Hybridizing Beam-ACO with Constraint Programming for Single Machine Job Scheduling
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Solving a bi-objective flowshop scheduling problem by pareto-ant colony optimization
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ant colony algorithm for traffic signal timing optimization
Advances in Engineering Software
Engineering Applications of Artificial Intelligence
Scheduling with an outsourcing option on both manufacturer and subcontractors
Computers and Operations Research
Refining scheduling policies with genetic algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A method for avoiding the searching bias in ACO deceptive problem solving
Web Intelligence and Agent Systems
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This paper deals with the scheduling problem of minimizing the makespan in a permutational flowshop environment with the possibility of outsourcing certain jobs. It addresses this problem by means of the development of an ant colony optimization-based algorithm. This new algorithm, here named as flowshop ant colony optimization is composed of two combined ACO heuristics. The results show that this new approach can be used to solve the problem efficiently and in a short computational time.