Ranking Dispatching Rules by Data Envelopment Analysis in a Job Shop Environment

This paper uses Data Envelopment Analysis (DEA) to measure multiple performance criteria for 42 dispatching rules in a job shop environment. We introduce a DEA application in production scheduling. Seven performance measures are considered in the evaluation. Without pre-assigning weights to any performance measure, DEA evaluates the efficiency of each dispatching rule relative to the other rules. After running a large number of experiments, the results show that two extreme subgroups of dispatching rules perform consistently. The shortest processing time related rules form the top group, while the longest processing time related rules form the bottom group. The due date or slack-related rules perform well in tardiness. However, they are ranked low if all seven criteria are considered together. The results provide guidance to scheduling practitioners in choosing priority dispatching rules when there are multiple objectives.

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