JIT供应模式下短驳合并运输集成优化模型

发布时间：2018-06-02 04:41

本文选题：JIT + 供应物流　；参考：《青岛大学》2014年硕士论文

【摘要】：随着物流管理意识的增强和现代物流业的发展,企业对于物流成本的关心日渐重视。降低物流成本是企业物流管理实践的首要任务。供应物流是物流系统中独立性较强的子系统,和生产系统、财务系统等制造企业各部门以及企业外部的资源市场、运输部门有密切的联系,对企业生产的正常、高效运作发挥重要作用。企业供应物流不仅要实现保证供应的目标,而且要在低成本、少消耗、高可靠性的限制条件下来组织供应物流活动,组织管理难度较高。因此,如何降低供应物流的成本,提高物流服务的水平,实现供应链整体优化成为制造企业提升竞争力的关键因素之一。针对及时化(Just in time,JIT)模式的供应物流短驳合并优化问题,建立了供应物流系统的短驳合并运输优化模型,同时利用基于递降最佳适合(Best Fit Decreasing, BFD)思想的启发式算法和改进的单亲遗传算法(Partheno Genetic algorithm, PGA)分别求解,并分析了此运作模式下的供应物流的成本和效率。单亲遗传算法没有采用传统遗传算法的交叉算子,仅仅在一条染色体上进行基因换位操作,即使种群中各个个体均相同,它也可以通过基因换位、基因倒位等遗传算子来实现遗传迭代,初始群体不需具有广泛多样性,“早熟收敛”的现象也就不会存在,因此该算法具备一定优势。以某汽车制造厂的供应物流数据为例进行计算机仿真实验。仿真结果表明,PGA算法求出的供应成本明显降低,比BFD启发式算法和TGA算法更具优势。该算法在解决供应物流中短驳合并运输问题时更加快速有效,可有效降低企业成本,提高经济效益。
[Abstract]:With the enhancement of logistics management consciousness and the development of modern logistics industry, enterprises pay more and more attention to logistics cost. Reducing logistics cost is the primary task of enterprise logistics management practice. Supply logistics is a subsystem with strong independence in the logistics system. It is closely related to various departments of manufacturing enterprises, such as production systems and financial systems, as well as to the external resource markets of enterprises, and transportation departments are closely related to the normal production of enterprises. Efficient operation plays an important role. Enterprise supply logistics should not only achieve the goal of ensuring supply, but also organize supply logistics activities under the condition of low cost, less consumption and high reliability, which is difficult to organize and manage. Therefore, how to reduce the cost of supply logistics, improve the level of logistics services, realize the overall optimization of supply chain has become one of the key factors to enhance the competitiveness of manufacturing enterprises. Aiming at the supply logistics short barge merger optimization problem based on the "just in time" mode, a short barge combined transportation optimization model of supply logistics system is established. At the same time, the heuristic algorithm based on the idea of descending Best Fit Decreasing, BFD) and the improved Partheno Genetic algorithm, PGA) are used to solve the problem, and the cost and efficiency of supply logistics under this operation mode are analyzed. The parthenogenic genetic algorithm does not use the crossover operator of the traditional genetic algorithm, but only performs gene transposition on one chromosome, even if each individual in the population is the same, it can be transposed through the gene. Genetic operators such as gene inversion to achieve genetic iteration, the initial population does not need to have extensive diversity, "premature convergence" phenomenon will not exist, so the algorithm has certain advantages. Taking the supply logistics data of an automobile factory as an example, the computer simulation experiment is carried out. The simulation results show that the supply cost of the algorithm is obviously reduced, which is superior to the BFD heuristic algorithm and the TGA algorithm. The algorithm is faster and more effective in solving the problem of short barge merging transportation in supply logistics, which can effectively reduce the cost of enterprises and increase economic benefits.
【学位授予单位】：青岛大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F253.7;TP18;F426.471

【参考文献】