Dynamic Controls of Genetic Algorithm Scheduling in Supply Chain
Jia Yee Chai*, Tatsuhiko Sakaguchi**, and Keiichi Shirase*
*Graduate School of Engineering, Kobe University, 1-1 Rokkodai, Nada-Ku, Kobe 657-8501, Japan
**Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku-cho, Toyohashi-shi, Aichi-ken 441-8580, Japan
In a supply chain environment, reactive scheduling process has to deal with both operational objective (minimizing total tardiness) and business objective (accommodating a new order into the current schedule). Genetic algorithm (GA) optimization has been applied in such reactive scheduling problem for job shop style manufacturer in our previous researches. An algorithm is introduced to dynamically adjust the objective function of GA optimization to minimize cost of delay penalties and to maximize the number of contracts captured by the manufacturer. The effectiveness of the proposed model is demonstrated by computational experiments.
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