Vehicle Routing Problem with Soft Time Window for Concurrent Bi-Directional Logistics

碩士 === 國立中央大學 === 土木工程研究所 === 93 === Abstract The introduction of reverse logistics may significantly reduce the cost of returned merchandise, improve the customer’s satisfaction, and therefore increase enterprise profit. Recently, most of enterprises pay their great attention to the inclusion of...

Full description

Bibliographic Details
Main Authors: WEN-CHING SU, 蘇文清
Other Authors: How-Ming Shieh
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/82379886639362879885
Description
Summary:碩士 === 國立中央大學 === 土木工程研究所 === 93 === Abstract The introduction of reverse logistics may significantly reduce the cost of returned merchandise, improve the customer’s satisfaction, and therefore increase enterprise profit. Recently, most of enterprises pay their great attention to the inclusion of reverse logistics to proceed hand in hand with already regularly-operated forward logistics. Transportation of physical distribution plays a critical role in logistics. In general, transportation cost is the majority of the total cost in supply chain, fifty-two percent approximately. The principal objective of the study is therefore to concurrently accomplish the delivery and pickup commodities at customer’s specified time window, i.e. to perform forward and reverse logistics at the identical trip. It may be classified as a vehicle routing problem with soft time window for simultaneous commodity delivery and pickup. The traditional vehicle routing problem is mostly considered the single object, the total distance, however the operation of companies is based on multiple objects rather than a single object. Therefore this study is to integrate the shortest distance and the fewest penalty cost by the weighting method in terms of both the cost and the level of service. This study suggested that pickup during the delivery only requires the rest capacity enough for the goods. There is no such constraint that pickup only can be performed when the certain capacity of the car is left. We solved the modified Solomon benchmark with random pickup demand by using Genetic Algorithms with soft time window (The penalty is dramatically increased by increasing the time of being late and waiting to emphasize the value of time for customers). In addition, we program a computer to demonstrate the accuracy of this idea. The results showed that total cost was slightly increased by increasing the demand of pickup and the cost was increased maximally about 6.44% when the quantity of pickup was about half of that of delivery. As a result, the idea, pickup during the delivery, actually improved the efficiency of the vehicle usage and reduced the waste of the capacity of returned vehicles.