Multi-Objective Vehicle Routing Problem for Cold Chain Industry Using Genetic Algorithm
碩士 === 國立臺中科技大學 === 流通管理系碩士班 === 103 === In order to reduce the threatening effects of global warming, all enterprises must face and deal with the problem of carbon emission carefully. This study proposes a mechanism to solve the multi-objective vehicle routing problem for the cold chain industry. B...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2015
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| Online Access: | http://ndltd.ncl.edu.tw/handle/973626 |
| Summary: | 碩士 === 國立臺中科技大學 === 流通管理系碩士班 === 103 === In order to reduce the threatening effects of global warming, all enterprises must face and deal with the problem of carbon emission carefully. This study proposes a mechanism to solve the multi-objective vehicle routing problem for the cold chain industry. Both the total carbon emission and the total travel distance are minimized. A genetic algorithm (GA) is employed to find the solutions.
The proposed mechanism is divided into two-stages. At the first stage, a k-means clustering algorithm is used to group customer locations. At the second stage, GA is employed to find out the minimized CO2 emissions and the minimized delivery routes with shortest travel distances. The proposed approach is demonstrated experimentally by a variety of scenarios of a famous cold chain company in Taiwan. The experimental results show that GA can find solutions effectively. In addition, the CO2 emissions according to a minimum emission objective in some cases may be less than those according to a shortest travel distance.
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