A Comparative Study of Different Operation Models for Capacitated Vehicle Routing Problems

• Main Authors: Hao-Wei Huang, 黃浩維
• Other Authors: Fu-Shiung Hsieh
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/44867672434220777408

碩士 === 朝陽科技大學 === 資訊工程系 === 103 === Logistics is the management of the flow of goods between the point of origin and the point of consumption to meet requirements of customers. Transportation is an important part of logistics as it imposes considerable cost on goods and has a significant influence on competitive advantage of a company. How to reduce the costs and improve the profit of a company is an important issue. Vehicle routing is a critical factor in reducing transportation costs. Finding optimal vehicle routes offers great potential to efficiently manage fleets, reduce costs and improve service quality. An effective scheme to manage fleets and determine vehicle routes for delivering goods is important for carriers to survive. In the existing literature, a variety of capacitated vehicle routing problems (VRP) have been studied. However, most VRP that have been studied are based on different operation models. There is a lack of a comparative study on different operation models for capacitated VRP. In this paper, we aim to develop a decision support system to compare the performance of several different operation models of VRP. The goal is to provide an effective tool to support the decisions of logistics companies. To achieve this goal, we propose an operation model, formulate an optimization problem and develop solution algorithms based on Google Maps API. In our problem formulation, we consider a set of goods to be picked up and delivered. Each goods has a source address and a destination address. The vehicles to transport the goods have limited capacities, including the maximal weight a vehicle can be carried and the maximal distance a vehicle can travel. The problem is to minimize the routes for picking up and delivering goods. The emerging Google Maps API provides a convenient package to develop an effective vehicle routing system. In this paper, we develop a vehicle routing algorithm by combining a discrete particle swarm optimization (DPSO)[46] method with Google Maps API. We compare the performance of different operation models based on our algorithms by numerical examples.