Dynamic Zoning Strategies for Dispatching of Couriers under Different Demand Patterns

• Main Authors: Yueh, Chung-Chieh, 岳忠傑
• Other Authors: Han, Fu-Wha Anthony
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/81814324587962838275

碩士 === 國立交通大學 === 運輸科技與管理學系 === 97 === This research is concerned with the dynamic dispatching of multiple couriers in a fixed region with the demand patterns which are influenced by temporal and spatial characteristics. Although abundant literature can be found on dynamic routing and dispatching problems, little has considered the impact of various demand patterns to the optional dynamic routing and dispatching. In our research, we consider both temporal and spatial characteristics of different demand patterns. Temporal characteristics include uniform, single peak-hour and double peak-hour distributions over a day of operation; spatial characteristics include uniform and cluster distributions over the service area. The dynamic zoning procedure, as we proposed, starts with a dynamic wait. Two dynamic waiting strategies are considered: DM which waits for M demand calls, and DW which waits a fixed time interval of W. As to the dynamic zoning, we first use the k-medoids method to cluster demand points, and then the Voronoi graphs to define the service zone for each courier. In each service zone, the courier follows the nearest neighbor heuristic to service the customers. In addition, both the “single zone” and “fixed zone” strategies are also considered in order to evaluate the performance of the proposed “dynamic zone” strategy. Simulation models were built and coded in C# to analyze the performance of the three zoning strategies. We tested on a Intel(R) Core(TM)2 CPU 2.00GHz personal computer. Under various temporal and spatial situations, results showed that the dynamic zoning yielded the lowest average travel distance, and yet the highest average waiting time. On the other hand, the single zone strategy gives the lowest waiting time, and yet the longest average travel distance. If the customer can accept the average waiting time in 60 minutes, dynamic zoning strategies under DM or DW will save significant travel distance more than single zone or fixed zone strategies when the demand is uniformly distribution. In addition, dynamic zoning strategies which wait more at peak hours and wait less at off-peak hours perform better than other strategies in travel distance.