A combination of particle swarm optimization and heuristic algorithm for solving vehicle routing problem

• Main Authors: Fu Ren Hsieh, 謝富任
• Other Authors: Ruey Maw Chen
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/91213033296189347798

碩士 === 國立勤益科技大學 === 資訊工程系 === 101 === The industry develops vigorously, therefore aroused the growth of economy. Increasingly, the operation and development of logistics industry are prosperous. In operations research, a kind of scheduling problem is similar to logistics problem which is called vehicle routing problem (VRP). The VRP has been confirmed to NP-hard. Furthermore according to different conditions and restrictions, the VRP can be subdivided into many different types. Recently, the meta-heuristic algorithms have been widely applied to solve NP problems. And the particle swarm optimization (PSO) is one of the meta-heuristic algorithms. In this thesis, the proposed scheme is PSO-based and involve with other heuristics and local search for solving VRP and to optimize the scheduling result. In order to conveniently set the algorithm’s parameters and display the result the Graphical User Interface (GUI) is provided. In this thesis, the benchmark for experiment is the Capacitated Vehicle Routing Problem (CVRP) instances of OR Library. Finally, the simulate results will be compare with other researches. The simulate results indicate that the proposed scheme is sound for solving the VRP.