| Summary: | 碩士 === 國立東華大學 === 運籌管理研究所 === 102 === Nowadays, along with the change of consumption pattern、the shortening of life cycle and the diversity of consumer goods, the rapid development of consumer electronics products such as smartphones cause many brand companies to introduce different types of new products to the market. The manufacturing industries are rising challenging. However, most of such products come from the same suppliers. The make-to-order manufacturing plant can only select the suitable and profitable orders and arrange the production schedule for such selected orders due to the limited plant capacity.
This study focuses on the maximizing profit in the make-to-order environment and study how to select the orders via the optimization approach based on the plant resources, the order profits, and the tardiness penalties. Also, these selected orders are scheduled to the parallel machines. The water flow-like algorithms, embedded with variable neighborhood search based on different types of neighborhood mechanisms, are proposed to solve the aforementioned problem and to discuss the tuning parameters of the algorithms. The two kinds of water flow-like algorithms are compared, with other existing algorithms such as particle swarm optimization and harmony search, to find out their solution qualities in different sizes of problems. The computational results show that, in the large-sized problems, WFA.II is performing much better than WFA.I with a range of solution gaps, 0.45%~38.06%. WFA.II is also competitive as other existing approaches in the large-sized problems, with an extremely short range of solution gap, 0.17%~1.65%.
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