Scheduling in parallel machines environment using genetic algorithm
Effective scheduling of the production process improves the operational effi ciency. The objective of the scheduling is to meet the due date, maximum utilization of resources, reducing work in process inventory and improving manufacturing lead time etc,. Scheduling in the multi objective criteria is the crucial task but necessary to achieve the better operational effi ciency in the competitive environment. When the complexity of the problems increases, it is the challenging process to obtain the optimum solution using mathematical or heuristic process alone. However application of genetic algorithm in scheduling process make easy to obtain the better and quick solution in the real environment. This paper uses the genetic algorithm for scheduling of jobs in the parallel machines production process. The algorithm is coded in MATLAB, and the objective functions are, minimum penalty cost, minimum machine idleness cost and combination of minimum penalty and machine idleness cost for comparison and discussion. The algorithm is tested for convergence, consistency and computational time.
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