中小城市农超对接配送中心选址与配送路径优化研究

发布时间：2018-06-06 19:07

本文选题：农产品物流 + 农超对接　；参考：《长安大学》2017年硕士论文

【摘要】：作为农产品流通方式的一种创新形式,“农超对接”是近几年出现在农产品供应链管理中的新方法。利用这种方法把现代流通方式引入农村,搭建市场经济中产销一体化服务链,达到商家、农民和消费者共赢的局面。在国内大型超市和农民专业合作社不断发展及不断学习国外先进流通经验的基础上,国内“农超对接”一直处于良好的发展状态。为了更好地完善城镇功能布局,推动农村消费市场开发,目前急需在中小城市逐步推进“农超对接”建设,这也正是本文研究的出发点。本文在总结当前“农超对接”发展模式的基础上,结合各地中小城市的实践和对文献的研究,认为中小城市开展“农超对接”,由于城市规模相对较小,运输需求又相对分散,提出构建中小城市“农超对接”物流云配送平台,解决当前中小城市物流管理观念落后和缺乏有效合作的问题。对中小城市“农超对接”物流配送节点布局、中小城市“农超对接”配送平台物流资源配置和中小城市“农超对接”配送平台网络结构与流程进行详细研究。在此基础上,考虑到中小城市收益相比较低,同时需要提升配送的满意度以及培养客户忠诚的要求,建立追求配送总成本最优的上层规划模型,配送满意度最大的下层规划模型的中小城市“农超对接”的双层规划模型。模型求解运用分枝定界法寻找最佳选址方案,配送中心的合理选址达到降低配送成本及满足配送服务时间要求的目标。配送中心建立基于新鲜度控制的路径优化模型,并运用粒子群算法求解带软时间窗限制的路径优化模型。实证分析将构建的双层规划模型运用到某中小城市“农超对接”实际中,结合中小城市配送规模收益相对较低,预算有限的约束,从配送成本最低和配送满意度最优为研究对象,在众多方案中最终选择两处建立配送中心。实践体现了规划选址模型的有效性,结合模型特点,运用分枝定界法和粒子群算法求解,有效提高了计算效率。
[Abstract]:As an innovative form of circulation of agricultural products, "agricultural super docking" is a new method in supply chain management of agricultural products in recent years. This method is used to introduce the modern circulation mode into the countryside, to build the integrated service chain of production and marketing in the market economy, so as to achieve the win-win situation among merchants, farmers and consumers. On the basis of the continuous development of large supermarkets and farmers' professional cooperatives in China and the continuous learning of advanced foreign circulation experience, the domestic "agricultural super docking" has been in a good state of development. In order to perfect the function layout of cities and towns and promote the development of rural consumption market, it is urgent to promote the construction of "agricultural super docking" in small and medium-sized cities, which is the starting point of this paper. On the basis of summing up the current development mode of "agricultural super docking", combining the practice of small and medium-sized cities and the research of literature, this paper thinks that the small and medium-sized cities carry out "agricultural super docking", because of the relatively small scale of cities, the transportation demand is relatively dispersed. In order to solve the problems of backward concept of logistics management and lack of effective cooperation, the paper puts forward the construction of logistics cloud distribution platform of "agricultural super docking" in small and medium-sized cities. This paper studies in detail the distribution node layout of the "agricultural super docking" logistics distribution in small and medium-sized cities, the allocation of logistics resources of the "agricultural super docking" distribution platform in small and medium-sized cities and the network structure and process of the "agricultural super docking" distribution platform in small and medium-sized cities. On this basis, considering the relatively low returns in small and medium-sized cities, and the need to improve the satisfaction of distribution and the requirement of cultivating customer loyalty, the upper planning model is established to pursue the optimal total cost of distribution. Distribution satisfaction of the lowest programming model of the medium and small cities "agricultural super docking" bilevel programming model. The method of branch and bound is used to find the best location scheme. The reasonable location of distribution center can reduce the cost of distribution and meet the requirement of distribution service time. A path optimization model based on freshness control is established and particle swarm optimization algorithm is used to solve the path optimization model with soft time window. The empirical analysis applies the bilevel programming model to the practice of "agricultural super docking" in a small and medium-sized city, combining with the constraints of relatively low distribution scale income and limited budget in small and medium-sized cities. Based on the lowest cost of distribution and the optimal distribution satisfaction, two distribution centers were selected in this paper. The practice shows the validity of the planning site selection model. Combining with the characteristics of the model, the branch and bound method and particle swarm optimization algorithm are used to solve the problem, and the computational efficiency is improved effectively.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F326.6;F721;TP18

【参考文献】