A Hybrid Heuristic for Vehicle Routing Problem with Time Window Constraints

• Main Authors: Pefo Cheng, 張寶豐
• Other Authors: James Chien-Liang Chen
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/01881213204828485657

碩士 === 中原大學 === 工業工程研究所 === 91 === This research proposes a heuristic, Enhanced Tabu - Perturbation Algorithm (ETPA), to efficiently and effectively solve Vehicle Routing Problem with Time Window Constraints (VRPTW). ETPA integrates Tabu Search (TS), Noising Method (NM) and Flip Flop Method (FF). TS is one of the most popular generic heuristics in solving VRPHTW in recent years. FF and NM are combinatorial optimization meta-heuristics. 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 ETPA. ETPA consists of three phases: initial solution construction, local search improvement, and generic 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 generic search improvement phase, a hybrid algorithm integrating TS, NM and FF is used to improve the initial solution. ETPA results in good solution quality and efficiency. The average deviation of distance is less than 3.9% and the average deviation of number of vehicles is about 9.5%, compared to the known “best” solutions. The average computation time is approximately 15 minutes to solve an instance.