碩士 / 國立高雄第一科技大學 / 機械與自動化工程研究所 / 105 / This study is focused on in-plant logistics in manufacturing. Owing to rising energy costs and supply-demand imbalance lead to price competition, resulting in a sharp decline in profits, the business management is facing a severe test especially heavy industry. In practice the important decision-making in C company has rely on expert experience and existing knowledge, the lack of systematic thinking and technology applications, resulting in a waste of logistics costs. Therefore, the study on application of genetic algorithms to optimization of steel mill factory by-product transport and logistics was presented. It is hoped to solve the bottleneck of traditional decision-making, so as to achieve the goal of optimizing transportation logistics decision-making by artificial intelligence.
In the definition of the problem, the model of the steel mill factory by-products transport and logistics is constructed through the in-plant route information, vehicle routing systematization and consideration of the transport demand frequency. The modified variable length chromosome coding technique and bi-level genetic algorithm are used to effectively solve the problem of different zoning transportation on genetic algorithm application. Experimental results show that the total transport time is slightly better than the existing results.
| Identifer | oai:union.ndltd.org:TW/105NKIT5689003 |
| Date | January 2017 |
| Creators | Hsi-I Hsieh, 謝錫毅 |
| Contributors | Tung-Kuan Liu, 劉東官 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 87 |
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