A Meta-Heuristic Method for Vehicle Routing Problem with Time Window Constraints

• Main Authors: Bai-Jie Chen, 陳百傑
• Other Authors: Chien-Liang Chen
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/21993520915168074947

碩士 === 中原大學 === 工業工程研究所 === 90 === ABSTRACT This research proposes a heuristic, Tabu-Disturbance Algorithm (TDA), to efficiently and effectively solve Vehicle Routing Problem with Time Window Constraints (VRPTW). TDA integrates Tabu Search (TS) and Noising Method (NM). TS is the most popular generic heuristic in solving VRPHTW in recent years and NM is a combinatorial optimization meta-heuristic. The first objective is to determine the route that minimizes the total vehicle travel distances. This leads to quick response to satisfy customer demands. The second objective is to find the minimum required number of vehicles. This can reduce the transportation cost. Solomon’s 56 benchmark instances were tested for TDA. TDA consists of three phases: initial solution construction, local search improvement, and disturbed search improvement. In the initial solution construction phase, enhanced Nearest Neighbor Method is used. In the local search improvement phase, vehicles reduction and Neighborhood Search modules are proposed. In the disturbed search improvement phase, a hybrid algorithm of TS and NM is used to improve the initial solution. TDA results in good solution quality and efficiency. The average deviation of distance is less than 3% and the average deviation of number of vehicles is about 9.5%, compared to the known “best” solutions. The average computation time is approximately 8 minutes to solve an instance.