On the Study of Improved Imperialist Competitive Algorithm to Solve the Capacitated Vehicle Routing Problem in Logistics Management

• Main Authors: Yung-Hsien Wang, 王詠賢
• Other Authors: Shih-Che Lo
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/82664986583860366231

碩士 === 國立臺灣科技大學 === 工業管理系 === 101 === Enterprises want to make profits in the extremely competitive environment. In addition to expanding sales and reducing manufacturing cost, the efficiency of logistics management is also considered as the additional source of profit. Increasing efficiency of logistics becomes critical in the supply chain due to customer’s quick response requirements. Therefore, lean logistics is considered a new thinking to decrease the number of the dispatched vehicles and reduce the fixed cost of the company. This thesis focuses on the vehicle routing problem with lean principles aiming at finding the shortest routes by using the minimum number of vehicles and shortest travel distance. A novel algorithm, called the Improved Imperialist Competitive Algorithm (IICA), is proposed in thesis to solve the combinatorial optimal solution for the Capacitated Vehicle Routing Problem. The IICA method is based on the new developed Imperialist Competitive Algorithm combined with the sweep method to quickly generate a near optimum solution. Comparisons are made between the IICA method and the Genetic Algorithm (GA) over the experiments of different capacitated benchmark problems to validate the performance of the IICA. Experiment results show that the IICA was able to discover new solutions than the GA for all 60 benchmarks problems. Also, the computational results show that the IICA is robust, converge fast and competitive with overall improvement of 7.78% over the GA.