Intelligent Engineering Systems through Artificial Neural Networks
42 Multiobjective Evolutionary Algorithm Approach for Job Shop Rescheduling Problem
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In recent years, rescheduling attracted considerable attention, motivated by both important practical issues and interesting research problems. In this paper we discuss a multi-objective rescheduling problem. A set of original jobs has been scheduled to minimize a given cost objective, and then several sets of new jobs arrive unexpectedly. The objective in the original schedule still needs to be minimized over all of the jobs. However, this will change the original schedule, reducing customer satisfaction and creating havoc with the original resource allocations. Thus, the tradeoff between the scheduling cost and the disruption cost must be considered in detail. We also propose a multi-objective evolutionary approach for solving this rescheduling problem. We use new representation method in the proposed algorithm. Advanced genetic operators adapted to the specific chromosome structure and the characteristics of the rescheduling problem are developed. Some practical test instances will demonstrate the effectiveness and efficiency of the proposed algorithm.