Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
Job Shop Scheduling with Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Manufacturing Control Problems are still often solved by manual scheduling, that means only out of the workers experience. Modern algorithms, such as Ant Colony Optimization, have proved their capacity to solve this kind of problems. Nevertheless, they are only used exceptionally in real world. There are two main reasons for that. Firstly, an ant-based scheduling tool has to fit into the organizational structures of today's companies, i.e. it has to be coupled with the Enterprise Resource Planning-system (ERP-system) used in the company, in order to ensure that the capacity of the colonies search is used as efficiently as possible. The second reason is the size of the real world shop floor scheduling problems. In order to be able to deal with that problem, the authors propose a continuously operating Ant Algorithm, which can easily adapt to sudden changes in the production system.