Strategies for Dynamic Vehicle Dispatching under Different Demand Patterns

• Main Author: 賴育廷
• Other Authors: Anthony F. Han
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/92214734048493282089

碩士 === 國立交通大學 === 運輸科技與管理學系 === 94 === Along with the development of technologies, the competitions between supply chain companies rely mainly on their services of fast delivery. In the real-world situation, the demands from customers are often received during the day of operation, and therefore the static route plan may not be able to meet our need. In this context, most researches have focused on the Dynamic Vehicle Routing Problem (DVRP) over the last decades. Different strategies have been proposed by scholars, being compared under specific demand pattern for each strategy, and it makes difficulty in deciding which strategies to be used under a general situation. In this thesis, the Dynamic Traveling Salemans Problem (DTSP) with single vehicle is considered as the basis. We focus on choosing adaptive strategies under different demand patterns, with temporal and spatial characteristics. Temporal characteristics consider uniform and peak time demand intensity over a day of operation, while spatial characteristic are uniform and non-uniform distributions of demands over different parts of the network. In our dynamic dispatching strategies, two kinds of basic route plans, NN (Nearest Neighborhood) and FCFS (First Come First Service), are considered. In combination with the route plans, five real-time dispatching concept (Basic, Reposition, Diversion, DDR, and DFR) are proposed. We use the C++ programming language to construct a simulation model for generating different scenarios of patterns and testing various strategies. The results show that each strategy performs observably differently. For the situation that a vehicle cannot accept another order after dispatched and on the way to reach a customer, the Reposition strategy can reduce the response time efficiently, with increasing the travel cost correspondingly. In contrast, the DDR strategy cuts the response time even more with less increase in overall travel cost. Therefore, the DDR strategy is suggested if the emphasis is on the Quality of Service. When there are no restrictions on the sequences of demand pickups, Diversion strategy is the only one which could simultaneously save both the response time and travel cost, under all demand patterns tested. The DFR strategy would require higher travel cost, but it could save a high percentage of response time among all proposed strategies, and therefore producing the best quality of service. In particular, it can save both the response time and travel cost under the situation of peak time interval and high demand intensity. Therefore, the DFR strategy is suggested if we put emphasis on quality of service, while the Diversion strategy should be used if we want to reduce operation cost. Keywords: Dynamic traveling salemans problem, Vehicle dispatching, Dispatching strategy, Heuristics.