A Multiple Ant Colony Optimization with Territorialism For Logistics Support Systems

• Main Authors: Jun-Jer You, 尤濬哲
• Other Authors: T.P. Liang
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/10417118824178340161

博士 === 國立中山大學 === 資訊管理學系研究所 === 103 === Logistics is an important issue for business activities. We need more efficient logistics to reduce the time of goods transportation. This becomes more important in the electronic commerce age, when the consumers demand quick delivery of their orders. Traditionally, merchandise delivery falls in the travelling salesman problem (TSP) or the vehicle routing problem (VRP). Numerous papers have been published in these two areas. However, most previous research did not take route balance into their models, which restrict their practical applicability. In reality, route balance is an important concern. Thus, in this study, we propose a revised ACO (ant colony Optimization) called MACOT (Multiple Ant Colony Optimization with Territorialism) that adds three features to include Multi Colony, Competition and Territorialism into ACO to find the shortest path under the condition of balancing the route simultaneously. To examine the performance of MACOT, we compared it with some datasets such as the random map, mTSP, CVRP from priors’ research. Our result shows that MACOT had an advantage over the existing methods, especially when the number of nodes growing. We developed a prototype logistics support system and evaluate it with data provided by a case company. Four indicators were used assess the performance of the system. The proposed system performed well in this real-world data test. This indicates the contribution of MACOT.