基于机群完好率的航材库存优化模型

针对航空兵部队航材配置不合理导致装备完好率不高的问题,分析了机群完好率与单机使用可用度之间的关系,建立了单机使用可用度及航材库存费用计算模型.以机群完好率为约束,以航材库存费用最低为目标,建立了基于机群完好率的航材库存优化模型,并给出了运用边际分析方法求解模型最优解的具体步骤.最后结合算例验证了模型的有效性.     

基于ERP的(s,S)策略下库存优化控制决策支持系统

针对当前ERP软件系统无法动态地给出优化订购策略并对历史数据进行有效的分析等不足,以最小化库存费用为目标建立起折扣准则下库存优化数学模型,对ERP软件中导出的各类历史数据进行模型化分析,动态地得出各类产品(s,S)结构形式的优化订购策略.基于该模型设计并开发了库存优化控制决策支持系统,为用户提供决策支持,很大程度降低了企业库存费用.     

典型串并联系统的备件库存优化模型

选取典型串并联系统的备件库存优化为研究对象,以系统供应可用度最大为目标,备件总购置费为约束条件构建备件库存优化模型,给出基于边际分析法的优化算法.经示例分析,验证了该模型的可行性和有效性,结果可为备件保障经费的合理配置提供理论依据.     

生鲜农产品双渠道供应链库存合作策略研究

随着我国"互联网+农业"战略的不断推进,生鲜农产品的网络销售渠道呈现出快速增长的趋势,但是生鲜农产品易腐易损、贮藏周期短、流通损耗大的特点在一定程度上加大了其网络销售渠道的运作难度.为此,从生鲜农产品传统销售渠道与网络销售渠道的库存协调与合作的视角,针对生鲜农产品双渠道供应链系统的特性,运用系统动力学的理论与方法构建了双渠道供应链库存独立系统、单级库存合作系统和多级库存合作系统的动力学模型.通过系统模型的仿真模拟,结果表明零售商与网络配送点进行库存紧急调拨的单级库存合作系统在牛鞭效应、服务水平和供应链总成本三个指标上表现最优,在供应链总库存指标上表现次优,整体上是最优的,并针对模型仿真结果,有针对性的提出对策与建议.     

安全因子优化与协调模型研究

在需求和供应都不确定的情形下 ,通过模型研究对两阶供应链的安全因子优化与协调作了一些有益的探讨 .本文引入了有效库存水平的概念 ,以反映上游缺货对下游库存的影响 ,在基准库存水平补货模式下构造了的供需双方的库存模型 ,且对安全因子进行整体优化以降低供应链的库存成本 .     

带短期价格折扣和允许两次特殊补货的库存决策模型

针对供应商提供短期价格折扣且允许零售商两次特殊补货的库存系统, 建立了以零售商库存效益最大化为目标的库存决策模型, 分析了模型的性质, 根据经济订单批量补货决策下补货时间点与折扣时段的关系, 确定了零售商在不同补货策略下的库存效益增值函数. 据此给出零售商相应的最优补货策略函数表达式, 提出了该模型的一个全局优化算法, 并通过数值算例验证了模型和算法的有效性与可行性.     

模糊环境下可控提前期供应链库存优化的Stackelberg模型研究

为了有效地缩短提前期与降低库存成本,研究了模糊环境下可控提前期的供应链库存优化问题.利用三角形模糊数描述需求的不确定性,建立了一类模糊需求条件下可控提前期供应链库存优化的Stackelberg模型.利用三角形模糊数描述成本系数的不确定性,建立了模糊成本系数条件下可控提前期供应链库存优化的Stackelberg模型,并提出利用均值面积度量法来解模糊化.通过数值分析来验证两类模型的优化效果.     

三级备件保障系统下的备件库存优化模型

目前我军装备备件保障通常采用三级保障模式,以各级备件期望短缺数量之和最小为目标,研究在不同库存水平条件下,三级备件保障系统的备件库存优化模型.经示例分析,验证了该模型的可行性和有效性,该结果可为多级备件保障提供理论依据.     

考虑风险偏好的动态生产库存问题的鲁棒优化模型

不同阶段需求不确定情况下,决策者的风险偏好和生产过程中的废品处理影响着供应链生产库存管理和供应链整体效益。本文考虑决策者风险偏好下,构建了包含I个生产者企业,一个库存点和一个废物处理基地的T阶段动态供应链生产库存框架,建立了椭球型需求不确定集下,以追求整体收益最大化为目标的不确定优化模型,并应用鲁棒优化理论得到了数据确定性线性鲁棒对应模型,讨论了模型解的可靠性和有效性。最后的算例表明,只有当决策者风险偏好参数在一定范围内时,才会存在满足条件且具有较高可靠性的鲁棒决策,验证了该鲁棒优化模型的合理性。     

基于排队的两类顾客易逝品库存控制策略研究

本文采用排队理论在面向两类顾客需求的环境下讨论易逝品库存排队系统控制策略问题。首先刻画面向两类顾客服务且具有马尔科夫结构的易逝品库存系统排队模型,获得库存水平状态的稳态概率分布以及作为库存成本控制的系统稳态性能指标。接下来,构建库存控制成本函数及考虑服务水平约束的库存控制优化模型,设计了改进的遗传算法。最后,数值算例揭示出系统参数的敏感性和相应的管理启示。     

突发事件情景下串联式需求系统应急物资协同调度研究

针对突发事件情景下串联式需求系统遭受破坏问题,分析了突发事件情景下串联式需求系统应急物资协同调度的特征。在对系统提供应急物资进行修复的基础上,以串联式需求系统修复的时间最短及成本最小为目标,分别构建了纵向配送的应急物资调度模型和纵向配送与横向转运相结合的应急物资协同调度模型,并设计一种遗传算法对两种模型进行求解。最后通过算例分析,求解得到两种模式下串联式需求系统应急物资调度的最优配送方案,比较解的结果,得出纵向配送与横向转运相结合的应急物资协同调度模式优于一般的应急物资纵向配送模式的结论,验证了该应急物资协同调度模式的有效性和可行性。     

三级供应链合作利润博弈与分配机制构建

基于变形需求函数建立了多向主从式三级供应链下游成员合作利润博弈模型,运用Stackelberg博弈法求解,对成员及渠道利润随合作关系程度变化进行深入的经济分析;构建了具有理性、转移性、协商性的供应链下游合作利润分配机制定量模型,其由合作利润结构性分配和合作利润运行性分配组成,阐明了之间的互动关系与内在运行方式,得出当合作关系程度高于2/3时才进行合作利润运行性分配的结论,且对分配机制的内在运行方式进行了数学解析。     

Capacity allocation problem with random demands for the rail container carrier

In this paper, we consider the formulation and heuristic algorithm for the capacity allocation problem with random demands in the rail container transportation. The problem is formulated as the stochastic integer programming model taking into account matches in supply and demand of rail container transportation. A heuristic algorithm for the stochastic integer programming model is proposed. The solution to the model is found by maximizing the expected total profit over the possible control decisions under the uncertainty of demands. Finally, we give numerical experiments to demonstrate the efficiency of the heuristic algorithm.     

Reservation and allocation policies for influenza vaccines

This research investigates the impact of alternative allocation mechanisms that can be employed in the context of vaccine inventory rationing. Available vaccine inventory can be allocated to arrivals from high priority (target groups such as healthcare professionals) and low priority (non-target groups) demand classes using Partitioned Allocation (PA), Standard Nesting (SN), and Theft Nesting (TN). In any one of the mechanisms, a part of the available inventory is reserved for the exclusive use of the high priority demand class. They differ, however, in how the unreserved portion of the inventory is utilized: Under PA, demand from the high (low) priority class consumes only the reserved (unreserved) quantity. Under SN, demand from the high priority class first consumes the reserved quantity; once and if this quantity is exhausted, high priority demand competes with low priority demand for the remaining inventory. Under TN the sequence of allocation is reversed: both demand classes first compete for the unreserved inventory. Once this portion of inventory is exhausted, high priority demand is fulfilled from the reserved inventory and low priority demand is rejected. We develop service level (probability of fulfilling the entire demand) and fill rate (fraction of demand fulfilled) expressions for all three allocation mechanisms. Based on these expressions, numerical analyses are conducted to illustrate which allocation mechanism a health planner should choose depending on the availability of vaccines, and how the health planner should set the reserved quantity for the high priority class. We observe that (1) there exist certain conditions under which one of the allocation mechanisms outperforms the others and (2) this effect is determined by the decision maker’s choice of the performance measure.     

Optimizing inventory decisions in a two-level supply chain with order quantity constraints

A fundamental assumption in traditional inventory models is that all of the ordered items are of perfect quality. A two-level supply chain is considered consists of one retailer and a collection of suppliers that operate within a finite planning horizon, including multiple periods, and a model is formulated that simultaneously determines both supplier selection and inventory allocation problems in the supply chain. It is supposed that the ordered products dependent on the suppliers include a certain percentage of imperfect quality products and have different prices. In this paper, we study the impact of the retailer’s financial constraint. On the other hand, suppliers have restricted capacities and set minimum order quantity (MOQ) policy for the retailer’s order amount happened in each period. So, the problem is modeled as a mixed integer nonlinear programming. The purpose of this model is to maximize the total profit. The nutrients, fishery and fruitage industries give good examples for the proposed model. A numerical example is presented to indicate the efficiency of the proposed model. Considering the complexity of the model, a genetic algorithm (GA) is presented to solve the model. We demonstrate analytically that the proposed genetic algorithm is suitable in the feasible situations.     

A resource portfolio planning model using sampling-based stochastic programming and genetic algorithm

Resource portfolio planning optimization is crucial to high-tech manufacturing industries. One of the most important characteristics of such a problem is intensive investment and risk in demands. In this study, a nonlinear stochastic optimization model is developed to maximize the expected profit under demand uncertainty. For solution efficiency, a stochastic programming-based genetic algorithm (SPGA) is proposed to determine a profitable capacity planning and task allocation plan. The algorithm improves a conventional two-stage stochastic programming by integrating a genetic algorithm into a stochastic sampling procedure to solve this large-scale nonlinear stochastic optimization on a real-time basis. Finally, the tradeoff between profits and risks is evaluated under different settings of algorithmic and hedging parameters. Experimental results have shown that the proposed algorithm can solve the problem efficiently.     

基于MAS协作机制的动态计算资源调度模型

针对网格环境的自治性、动态性、分布性和异构性等特征.提出基于多智能体系统(Mutil Agent System,MAS)博弈协作的资源动态分配和任务调度模型,建立了能够反映供求关系的网格资源调度模型和任务求解算法,证明了资源分配博弈中Nash均衡点的存在性、唯一性和Nash均衡解,该方法能够利用消费者agent的学习和协商能力,考虑和引入消费者的心理行为,使得消费者的资源申请和任务调度具有较高的合理性和有效性.实验结果表明,资源调度算法不但可以有效减少不必要的延迟,而且在响应时间的平滑性、吞吐率及资源利用率方面比传统算法要好,从而使得整个资源的供需合理、负载均衡.     

数理统计学在多阶段库存管理模型中的研究综述

多阶段库存问题是供应链管理的重要课题,基于数理统计学在临界值策略方面、需求分布函数估计方面、优化算法方面介绍了国内外多阶段库存管理模型模型的研究进展和现状.     

一种资源投入不确定情形下的合作博弈形式及收益分配策略

首先,将经典合作博弈进行扩展,提出了一类模糊联盟合作博弈的通用形式,涵盖常见三种模糊联盟合作博弈,即多线性扩展博弈、比例模糊博弈与Choquet积分模糊博弈.比例模糊博弈、Choquet积分模糊博弈的Shapley值均可以作为一种特定形式下模糊联盟合作博弈的收益分配策略,但是对于多线性扩展博弈的Shapley值一直关注较少,因此利用经典Shapley值构造出多线性扩展博弈的Shapley值,以此作为一种收益分配策略.最后,通过实例分析了常见三类模糊联盟合作博弈的形式及其对应的分配策略,分析收益最大的模糊联盟合作对策形式及最优分配策略,为不确定情形下的合作问题提供了一定的收益分配依据.     

A joint optimisation model for inventory replenishment,product assortment,shelf space and display area allocation decisions

In this paper, we propose an optimisation model to determine the product assortment, inventory replenishment, display area and shelf space allocation decisions that jointly maximize the retailer’s profit under shelf space and backroom storage constraints. The variety of products to be displayed in the retail store, their display locations within the store, their ordering quantities, and the allocated shelf space in each display area are considered as decision variables to be determined by the proposed integrated model. In the model formulation, we include the inventory investment costs, which are proportional to the average inventory, and storage and display costs as components of the inventory costs and make a clear distinction between showroom and backroom inventories. We also consider the effect of the display area location on the item demand. The developed model is a mixed integer non-linear program that we solved using LINGO software. Numerical examples are used to illustrate the developed model.