人工鱼群算法优化支持向量机的物流需求预测模型研究

物流需求受多种因素的作用,具有时变性和混沌性,针对当前支持向量机的参数优化难题,提出一种改进人工鱼群算浅优化支持向量机的物流需求预测模型.首先对原始物流需求数据进行混沌分析,挖掘出隐藏其中的物流需求变化规律,然后采用支持向量机对物流需求数据进行非线性建模,并采用人工鱼群算法搜索支持向量机的参数,最后利用某地区物流数据与当前经典模型进行性能对比测试.结果表明,模型预测精度.更高,更加客观地反映了物流需求变化特性.     

物流服务水平影响竞争产品需求的协调机制

考虑一个由两个竞争性制造商、一个第三方物流服务商以及一个零售商组成的供应链系统,其中制造商生产的产品互为替代品,产品的物流分销职能由第三方物流服务商承担,并且产品市场需求依赖于第三方物流服务商提供的服务水平.为了有效地激励第三方物流服务商提高服务水平,设计了物流服务成本共担机制,分析了分散式成本共享机制和集中式成本共享机制对供应链绩效以及成员的利润影响.研究结果表明在一定条件下物流服务成本共担机制能有效改进供应链绩效.     

基于精英单亲遗传算法的冷链物流VRP模型优化研究

针对冷链物流配送的特殊性,探索冷链物流车辆路径问题(VRP)优化方案.首先,在保证货物不超载的条件下,建立基于时间和品质因素的顾客满意度约束的多配送中心VRP(MDVRP)模型;其次,采用重心分区法和改进的精英单亲遗传算法,求解顾客在配送中心的分配,确定配送车辆数以及顾客服务次序;最后,用Matlab工具编程对模型进行求解分析.结果表明构建基于满意度的冷链物流MDVRP模型更适合冷链物流配送最优路径选择,并且改进单亲遗传算法能够有效求解这类问题.     

Minimizing Labor Requirements in a Periodic Vehicle Loading Problem

In this paper, we address a logistics problem that a manufacturer of auto parts in the north of Spain described to the authors. The manufacturer stores products in its warehouse until customers retrieve them. The customers and the manufacturer agree upon an order pickup frequency. The problem is to find the best pickup schedule, which consists of the days and times during the day that each customer is expected to retrieve his/her order. For a given planning horizon, the optimization problem is to minimize the labor requirements to load the vehicles that the customers use to pick up their orders. Heuristically, we approach this situation as a decision problem in two levels. At the first level, customers are assigned to a calendar, consisting of a set of days with the required frequency during the planning horizon. Then, for each day, the decision at the second level is to assign each customer to a time slot. The busiest time slot determines the labor requirement for a given day. Therefore, once customers have been assigned to particular days in the planning horizon, the second-level decision is a multiprocessor scheduling problem, where each time slot is the equivalent of a processor, and where the objective is to minimize the makespan. A metaheuristic procedure is developed for the problem of minimizing labor requirements in this periodic vehicle-loading problem and artificial as well as real data are used to assess its performance.     

运筹学在汽车零部件入厂物流中的应用

汽车物流包括供应物流(零部件入厂物流)、生产物流、销售物流和回收物流,其中零部件入厂物流因其技术性强、复杂度高,被公认为汽车物流系统良性运作的关键环节.在分析汽车零部件入厂物流的基础上,研究运筹学在汽车零部件入厂物流中的应用, 构建数学模型,并用贪婪算法求解.     

交易流动性不对等环境下基于收入共享契约的供应链协调

供应链中存在单一生产商、单一零售商和一个交易流动性不对等的第三方B2B电子交易市场。在零售需求不确定的情况下,分别建立了供应链集中决策模型、传统固定合约均衡决策模型、收入共享契约分散决策模型,验证了收入共享契约在多渠道采购环境下仍可以协调供应链,分析了使供应链达到帕累托改进的收入共享契约的参数设定,最后分别从卖出流动性和买入流动性两个角度讨论了交易流动性对供应链的影响。研究结果表明,卖出流动性好的电子交易市场可以促使供应链达到最优生产量,实现整体收益的最大化;两种交易流动性的趋好都会提高供应链效率,但生产商更偏好卖出流动性好的电子交易市场。     

基于体系工程与物流均衡的C2M服务制造物流体系结构模型

C2M服务制造是基于以顾客为中心的C2M(Customer to Manufacture)商业模式,是在服务型制造及生产性服务业为基础上而形成的一种新型产业模式。C2M服务制造要求构建合理的物流体系,而构建物流体系结构已经成为该研究的关键基础。本文基于体系工程和物流均衡理论,通过建立物流体系以解决C(客户)端与M(制造)端的短链式互联问题,在分析C2M服务制造物流体系特征和资源要素的基础上,给出了C2M服务制造物流体系的概念模型和结构模型,并运用价值函数分析体系状态是否优化,从而达到C端与M端快速互联的目标,进而解决了物流体系结构模型在C2M服务制造物流体系构建中的应用问题。     

随机需求下物流服务供应链订购策略研究

针对由单个物流服务提供商和集成商组成的物流服务供应链,基于集中化模式、纳什博弈模式和Stackelberg博弈模式三种典型模式,考虑市场需求随机且受服务质量缺陷承诺水平的影响,探讨物流服务供应链的订购与质量缺陷承诺策略问题。通过分析发现:物流服务质量缺陷承诺水平随着市场需求弹性系数的增加而递减,但其受物流服务集成商观测水平的影响却因合作模式不同而变化不一致;集中化模式下的物流服务订购量随着物流服务集成商观测水平或市场需求弹性系数的增大而递减,但在其他两种合作模式下物流服务订购量随着物流服务集成商观测水平或市场需求弹性系数的增加而增加;在三种模式下,物流服务供应链的整体利润随着市场需求弹性系数的增加而递减,但其受物流服务集成商观测水平的影响却因合作模式不同而变化不一致。     

多阶段并发的协同物流网络任务-资源集成调配模型

协同物流网络作为动态开放的网络需要整合多种资源,以完成多项并行的物流任务。为此,本文从物流服务集成商的角度,研究了带时间窗和资源约束的任务—资源集成调配问题。通过将物流任务分解为不同阶段,构造多阶段并发的协同物流网络任务—资源集成调配模型,并采用遗传算法对模型进行求解,以从候选资源集合中为任务阶段匹配合适的资源。算例结果表明,该模型能够有效实现N-N的任务-资源集成调配,使得协同物流网络的整体效益达到最优。     

Product allocation to different types of distribution center in retail logistics networks

We consider the problem of assigning stockkeeping units to distribution centers (DCs) belonging to different DC types of a retail network, e.g., central, regional, and local DCs. The problem is motivated by the real situation of a retail company and solved by an MIP solution approach. The MIP model reflects the interdependencies between inbound transportation, outbound transportation and instore logistics as well as capital tied up in inventories and differences in picking costs between the warehouses. A novel solution approach is developed and applied to a real-life case of a leading European grocery retail chain. The application of the new approach results in cost savings of 6% of total operational costs compared to the present assignment. These savings amount to several million euros per year. In-depth analyses of the results and sensitivity analyses provide insights into the solution structure and the major related issues.