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基于遗传算法的卷烟区域物流配送中心选址方法

Genetic algorithm-based site selection method for regional cigarette distribution centers

  • 摘要: 为提升烟草行业物流资源利用效率,发挥物流规模经济优势,降低行业物流运营成本,基于运输成本和运营成本核心指标构建了区域物流配送中心总成本模型,并采用遗传算法进行求解,给出了推荐的区域物流配送中心选址方案。仿真结果表明:①提出的区域物流配送模式能够充分整合烟草行业现有的物流资源,提升物流规模化效应,实现物流网络的高效运作;②区域物流配送模式相比于单点物流配送模式总成本减少了7.75%,实现了物流网络成本效益最大化;③提出的区域物流配送中心选址方法能够根据不同省份的地理和运营特点进行自适应调整,可为烟草行业物流网络布局规划提供技术支持。

     

    Abstract: To enhance the utilization efficiency of logistics resources in the tobacco industry, to take advantage of logistics economies of scale and to reduce the overall logistics operating costs, a total cost model for regional logistics hubs was developed based on the key indicators of transportation and operating costs. The genetic algorithm was used for selecting an optimal site of regional distribution center. The simulation results showed that: 1) The proposed regional logistics facility could integrate the existing logistics resources, elevate scale effects, and achieve high-performance network operations. 2) Compared with the single-point logistics distribution mode, the regional logistics distribution mode reduced the total cost by 7.75%, maximized the cost-effectiveness of the logistics network. 3) The proposed site selection approach for regional logistics distribution centers exhibited an ability of self-adaptive to the geographical and operational characteristics of different provinces, it provided a technical basis for logistics network planning in the tobacco industry.

     

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