The Optimization of the Path for Equipment Inspection and Routine Maintenance via Genetic Algorithms

• Main Authors: Kai –Ming Cheng, 鄭凱明
• Other Authors: Ching –Hsiang Lee
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/02509437359823007715

碩士 === 國立高雄應用科技大學 === 電機工程系博碩士班 === 101 === On the basis of the rise of the consciousness of customer service and the consideration of labor cost reduction, the best solution of the path for equipment inspection, urgent repair and routine maintenance through the genetic algorithms (GA) is studied in this thesis to ensure the normal equipment operation as well as the reduction of labor waist and overtime problem resulting the improvement of the production capacity. The research method is to solve the traveling salesman problem (TSP) through the application of the genetic algorithms (GA). Based on the basic principles and characteristics of the genetic algorithms and exploiting the effectiveness of the traveling salesman problem, Matlab software is adopted to solve the optimization problem. The study was done by selecting a Southern District Customer Service Center of a gas Industrial Co., Ltd. in Taiwan. By using the theory of TSP problem, the optimal path for equipment inspection, urgent repair and routine maintenance is found. The optimal path results in significant cost reduction and energy consumption during the routine inspection routes.