Incorporating Cargo Loading Feasibility into a B2B Delivery Vehicle Routing Problem

碩士 === 國立東華大學 === 運籌管理研究所 === 107 === In the supply chain management, the cost of transporting the cargo was account for a large part in the operation process. The efficiency distribution planning not only can save the cost, but also to increase the customer satisfaction. However, distribution plann...

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Bibliographic Details
Main Authors: Shi-An Lin, 林士安
Other Authors: Cheng-Chieh Chen
Format: Others
Language:zh-TW
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/563q7v
Description
Summary:碩士 === 國立東華大學 === 運籌管理研究所 === 107 === In the supply chain management, the cost of transporting the cargo was account for a large part in the operation process. The efficiency distribution planning not only can save the cost, but also to increase the customer satisfaction. However, distribution planning was much difficult in practice, especially in the loading problem. Three dimensional loading is an NP-hard problem. In the logistics company, they always face to a plight that they cannot load cargos into a specific vehicle completely, so that the workers have to reload again or use extra vehicle. In the past, we just consider the limit of weight or capacity of vehicle in CVRP problem, the results were hard to be executed in the real situation, and probably increased the extra operation cost and time. The main idea of this paper was to solve the 3L-CVRP problem by the proposed heuristics algorithms, based on “Routing first- Packing second” strategy. We used simulated annealing algorithm to find an initial solution of the improved CVRP problem and solve the loading problem based on CargoWiz software. The object was to minimize the number of vehicle used. And we took the real data of a B2B (Business to Business) logistics company for instance in this paper, that was rarely seem in before. The characteristics of B2B cargos were a wide variety and the qualities were so much different. Eventually, we found feasible solutions by the methods we proposed. The logistics company can follow our methods to make a distribution plan in advance to avoid the loading infeasibility.