APPLICATION OF ANT COLONY OPTIMIZATION FOR EFFECTIVE SCHEDULING OF CLH PROCESSES IN BHEL
2006
Ant Colony Optimization (ACO) is a meta heuristic proposed to derive approximate solution for computationally hard problems by emulating the natural behaviors of ants. We consider the problem of scheduling a number of jobs on a given machine against a restrictive common due date. One of the basic and significant problems, that a shop or a factory manager is encountered, is a suitable scheduling and sequencing of jobs on machines. One type of scheduling problem is job shop scheduling. There are different machines in a shop of which a job may require some or all these machines in some specific sequence. The objective is to minimize the makespan during the Constant Load Hanger (CLH) manufacturing processes. After optimizing the makespan, the job sequencing must be carried out for each machine. An ACO algorithm is developed with several specific features. We consider particularly the impact on existing scheduling and production system and qualitative improvements which results from the systems implementation
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