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http://dx.doi.org/10.9723/jksiis.2020.25.6.159

A Study of Cold Chain Logistics in China: Hybrid Genetic Algorithm Approach  

Chen, Xing (호남대학교 경영학과)
Jang, Eun-Mi (호남대학교 경영학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.6, 2020 , pp. 159-169 More about this Journal
Abstract
A cold chain logistics (CCL) model for chilled food (-1℃ to 8℃) distributed in China was developed in this study. The CCL model consists of a distribution center (DC) and distribution target points (DT). The objective function of the CCL model is to minimize the total distribution routes of all distributors. To find the optimal result of the objective function, the hybrid genetic algorithm (HGA) approach is proposed. The HGA approach was constructed by combining the improved K-means and genetic algorithm (GA) approaches. In the case study, three scenarios were considered for the CCL model based on the distribution routes and the available distance, and they were solved using the proposed HGA approach. Analysis results showed that the distribution costs and mileage were reduced by approximately 19%, 20% and 16% when the proposed HGA approach was used.
Keywords
Cold chain logistics; Distribution center; Distribution target point; Hybrid genetic algorithm; K-means algorithm;
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