Optimization of Dynamic Job-Shop Scheduling Based on Game Theory

Rui Wang; Guang Hui Zhou

doi:10.4028/www.scientific.net/AMM.373-375.1045

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Optimization of Dynamic Job-Shop Scheduling Based on Game Theory

Abstract:

To deal with uncertain dynamic interferences occurred in the workshop, and meet the competition requirements of jobs submitted by different customers, a dynamic job-shop scheduling model based on game theory is presented. In order to find the Nash equilibrium point of the model effectively, dynamic rescheduling judgment based on event-driven policy is adopted, and a hybrid genetic algorithm is designed. The case study is carried out to demonstrate the validity of above dynamic job-shop scheduling methods.