Scheduling Jobs with Values Exponentially Deteriorating over Time in a Job Shop Environment
نویسنده
چکیده
This study focuses on solving a special kind of job shop scheduling problem (JSP), where the job value is exponentially deteriorating over time. The current study attempted to find out whether the expected benefits of Lot Streaming (LS) can be found in solving the JSP with the objective of maximizing the total value of the jobs. LS is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. Since the studied scheduling problem is a complex problem, this study proposed an efficient technique comprised of a genetic algorithm (GA) for lot streaming and simple dispatching rules (SDRs) to maximize the total value of the jobs, in order to facilitate timely decision making. The experiments led us to conclude that the proposed technique is significantly superior over other approaches in terms of the total value of the jobs and the average number of sub-jobs in a job.
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