| Summary: | 碩士 === 國立高雄第一科技大學 === 系統資訊與控制研究所 === 97 === Global competitions and problems of the irregular demand pattern are challenging the manufacturing industry nowadays, and utilization of multi-objective genetic algorithm in production scheduling is suggested to improve the efficiency of traditional method in this research.
Most of the manufacturing production scheduling is mainly controlled by shop-flow, and scheduling results are not always proper or fully satisfied due to lack of professional techniques and experiences.
On the other hand, shop-flow is also required to take several scheduling goals of efficiency into considerations, and the goals are often contradictory.
That is to say that improving one of the goals would result in decreasing another goal of efficiency.
In this research, two case companies and three practical examples are represented to demonstrate how applications of multi-objective genetic algorithm in optimizing production scheduling successfully helped shop-flow to find the most efficient scheduling result and meanwhile provide the most proper solutions for decision makers.
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