摘要
为优化冷链物流配送路径,提高配送效率,实现低碳绿色出行,综合考虑顾客对农产品新鲜度的要求、冷链企业对物流成本的控制以及社会环境对碳排放的约束等方面,以生鲜农产品新鲜度和准时到达率量化客户满意度,以固定成本、运输成本、制冷成本和惩罚成本构成物流成本,以运输燃料消耗及制冷产生的CO_(2)计算碳排放量,提出带混合时间窗的生鲜农产品冷链物流配送路径多目标优化模型。基于带精英策略的非支配排序遗传算法(NSGA-Ⅱ)求解模型,得到Pareto解集,并结合层次分析法,选出最优满意解。以华北某地区情况为例,将NSGA-Ⅱ与NSGA对比,发现NSGA-Ⅱ的收敛速度较快且结果质量较高,各目标值较为理想,表明模型和算法的有效性与实用价值。
In order to optimize the distribution path of cold chain logistics, improve distribution efficiency, and achieve low-carbon green, by comprehensively considering the influence of customers’ requirements for freshness of agricultural products, the control of logistics costs by cold chain enterprises and the constraint of social environment on carbon emissions, this paper quantifies customer satisfaction by freshness and on-time arrival rate of fresh agricultural products, expresses logistics costs by fixed costs, transportation costs, refrigeration costs and penalty costs, and calculates carbon emissions by transportation fuel consumption and CO_(2) generated by refrigeration, and proposes a multi-objective optimization model for cold chain logistics distribution path of fresh agricultural products with mixed time windows. Based on the solution model of non-dominated sorting genetic algorithm with elite strategy(NSGA-Ⅱ), the Pareto solution set is obtained, and combined with analytic hierarchy process, the optimal satisfactory solution is selected. Taking the actual situation of a province in North China as a reference, NSGA-Ⅱ is compared with NSGA. It is found that NSGA-Ⅱ has fast convergence speed, high result quality and ideal target values. The result shows the effectiveness and practical value of the model and algorithm.
作者
常海平
李婉莹
董福贵
郭晓鹏
CHANG Haiping;LI Wanying;DONG Fugui;GUO Xiaopeng(School of Economics and Management,North China Electric Power University,Beijing 102206,China)
出处
《交通科技与经济》
2022年第2期8-17,共10页
Technology & Economy in Areas of Communications
基金
国家社会科学基金项目(19BJY074)。
