PRODUCTION SCHEDULING PROBLEM SOLVING USING GENETIC AND GREEDY ALGORITHMS WITH SEQUENCE- DEPENDENT SET-UP TIMES
Keywords:
Production Scheduling, Set-up Time, Genetic algorithm , Greedy algorithmAbstract
In today’s competitive markets, the importance of good scheduling strategies in manufacturing companies, lead to the need of developing efficient methods to solve complex scheduling problems. In scheduling attempt to fill the gap between scheduling theory and scheduling practice, with the aim to give answer to respond to market demand for more efficient method to solve complex scheduling problems. Although classical scheduling theory are one of the most studied field in Operations Research, some practical environments are often ignored in the classical models, since they improve the complexity of mathematical models. For discussion in the gap between scheduling theory and scheduling practice Main aim of this research work is to solve two production scheduling problems with sequence dependent setup times. The setup times are one of the most common complications in scheduling problems, and are usually associated with cleaning operations and changing tools and shapes in machines. The first problem considered is a single machine scheduling with release dates, sequence dependent setup times and delivery times. The performances measure is the maximum lateness. The second problem is a job shop scheduling problem with sequence dependent setup times where the objective is to minimize the make span. These two problems were addressed using genetic and greedy algorithm. There by, a highly efficient decoding procedure is proposed which strongly improves the quality of schedules. We present several priority dispatching rules for both problems, followed by a study of their performance.
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