带有时限的多点应急系统库存策略优化研究

主要研究有时限约束的应急供应系统的库存服务水平问题。考虑随机需求下的包含一个中央供应点和多个不同地方供应点的二级系统,当缺货发生时,基于就近原则的转运模式建立了有时限约束的地方供应点库存策略优化模型,在此基础上分析了随机转运和不转运两种模式对模型的影响,最后采用粒子群算法对模型进行求解和分析。结果表明:在有时限约束时,就近原则模式下的库存策略具有较高的服务水平,并且时限约束越紧,其优势越显著。     

多供应点、多需求点应急物资调运模型及算法

研究了多供应点、多需求点应急物资调运问题的优化目标、决策模型及求解算法。首先,从需求点的角度考虑应急物资的需求紧迫程度、运达时间和需求满足情况,提出了应急保障综合评价函数。在此基础上,兼顾不同供需情况以及应急物资和运输工具种类的多样性,构建了以应急保障综合评价函数值最小为目标的决策模型。最后,针对模型特点提出了嵌入解构造算法的改进粒子群优化算法(IPSOA-ESCA)。仿真实验验证了应急保障综合评价函数的合理性、模型的普适性和算法的有效性。     

应急资源多目标优化调度模型与多蚁群优化算法研究

大规模自然灾害发生后,极易出现多地同时提出多类型资源需求的局面.基于灾后应急资源调度的特点,建立了考虑多需求点、多供应点、多资源类型、且多个资源供应点能为多个资源需求点协同配备资源的多目标优化调度模型.模型中对调度路线的可靠度进行了考虑,增强了实用性.设计了求解模型的多蚁群优化算法,在全局信息素更新规则中引入精英策略,指导多蚁群间相互交换与共享信息,加快全局非劣解搜索效率.多目标多蚁群优化算法将资源定位配置与路线安排问题进行了集成解决.算例分析表明该算法能够很好地处理大型复杂网络.     

基于延迟转运的维修备件库存模型

通过分析单级多基地的维修备件库存状态转移过程,建立了维修备件延迟转运模型,给出了库存直接满足需求、横向转运满足需求及延迟转运满足需求概率的表达式;在此基础上构建了以库存持有成本、停机及转运费用之和最小为目标的库存模型,并构造了基于迭代的模型求解算法。通过算例验证了模型的正确性及算法的有效性。     

两级供应链联合成本三角模糊需求随机过程模型

根据影响两级供应链系统库存控制及决策过程的随机与模糊特性,基于联合成本提出两级供应链三角模糊需求随机过程模型。对两级供应链系统进行研究,给出其联合成本优化模型。针对交货时间和需求率的模糊特性,分情况利用三角模糊函数设计缺货数量模糊模型,基于此对两级供应链联合成本优化模型进行改进,建立三角模糊需求随机过程模型,并给出该模型的求解过程。通过模型参数敏感性实验以及算法对比实验,验证了所提模糊随机过程模型的有效性。     

应急资源调度的模糊规划模型

研究了出救点资源可用量及出救所需时间为三角模糊数的应急资源调度问题。以应急开始时间满意度和资源需求满意度最大为第一目标,出救点最少为第二目标构建资源调度模糊规划模型。设计了将此模型化为确定性规划模型,进而用分层序列法求解模型的方法。以算例展示了模型中各目标间的协调及模型的实用性、算法的合理性和有效性。     

基于需求链的海上应急物资协同调度方法研究

针对应急反应基地的物资储备量无法满足海上突发事件的物资需求及其运力无法满足在应急限制期内将应急物资一次性地运往事故点的问题, 提出三级应急物资协同调度的概念模型。同时考虑到海上应急物资调度的时间不确定性, 构建基于需求链的二阶段动态调度模型。第一阶段解决基于应急响应时间最短的应急反应基地到事故点的物资调配问题, 第二阶段解决基于运输成本最小的陆上供应点的动态物资供应问题。根据模型特点, 设计一种贪婪算法, 分两个阶段逐步构造完整的满意解。最后, 通过具体算例验证模型的合理性和有效性。     

考虑公平性的面向多灾点需求应急资源调度

针对铁路突发事件多需求点多供应点的应急资源调度问题,结合"软时间窗"的概念,以公平性最大和调度总成本最小为优化目标,设计了有多个救援目标的应急资源调度模型,并利用并列选择遗传算法求解。该算法根据目标函数的个数,将种群均等地划分为与目标函数个数相等的子种群,为划分后的各个子种群各自分配一个目标函数,并对其进行独立的选择运算,将各个子种群中适应度高的个体组成新的种群,对这个新的种群进行交叉、变异,生成下一代种群。算例表明,与粒子群优化（PSO）和两阶段启发式算法相比,利用并列选择遗传算法进行计算,目标函数中所有需求点的资源满足程度的方差分别减小了93.88%、89.88%,成本分别减少了5%、0.15%。所提算法能够有效减小所有需求点的资源满足程度的方差,即提高各需求点的公平性,同时降低成本,其在求解多目标规划问题中能够得到更优的解。     

铁路应急资源动态多阶段调度决策模型及算法研究

近年来,铁路突发事件时有发生,严重影响铁路的正常运营,合理地进行应急资源的调度是提高铁路整体应急救援能力,减少突发事件所造成损失的有效途径。以博弈论为理论基础,将各应急点看作博弈局中人,考虑救援点到应急点的运力限制以及不同资源在不同应急点的重要度等因素,构建了资源动态需求函数,并用应急点对资源缺少量的时间累积来刻画系统损失。将多应急点的资源调度描述为一个多阶段非合作博弈过程,以系统总损失最小为目标,建立多应急点-多救援点-多种资源的动态多阶段资源调度模型,并设计了求解该模型Nash均衡的改进布谷鸟算法,从而得到最优的铁路应急资源调度方案。通过具体算例验证了模型的可行性与算法的优越性。结果表明该模型较为切近实际、适用性较强且改进后的算法更具高效性,可为铁路应急资源调度决策提供依据和支持。     

救灾物资多阶段分配与调度问题建模与求解

救灾物资多阶段分配与调度问题是灾害应急决策中的一个难点问题.首先,基于三角模糊数描述发放点物资需求的不确定性, 并基于路段历史行程时间函数刻画交通路网的动态性,构建应急救援物资多阶段分配与调度模型;然后,基于蚁群优化搜索各储备点到各发放点的通行时间矩阵,引入NSGA-II搜索救灾物资分配和调度方案,设计救灾物资多阶段分配与调度集成优化算法和编码调整策略;最后,通过仿真实验验证所提方法的有效性.实验结果表明,所提方法可为决策者提供多种不同偏好的方案,从而为决策者提供更多的选择空间,契合应急场景.     

基于契约理论的服装双渠道利益协调建模与应用

为协调服装企业渠道间的利益关系,结合零售利益冲突成因,从利润最大化角度出发,依据需求服从均匀分布,分析批发价格契约与转运契约条件下,合作方式与订货量的变化对品牌企业、加盟商及零售整体的库存量、缺货量及利润等指标数据的影响,由此建立相关模型和事例解析.结果表明,相比批发价格契约,转运契约条件下,服装品牌企业与加盟商的库存量、缺货量明显降低,获利能力增加,同时可减少缺货损失和库存,实现双渠道收益共享.转运契约模型的应用可减少市场需求变动风险,促进服装供应链利益共享的实现.     

带有横向调度的维修备件选址库存路径问题研究

存储点的合理选址、库存的合理控制及运输配送的有效决策是支撑维修备件物流系统的重要内容。通过分析基于横向调度的维修备件物流系统,建立了基于横向调度的维修备件库存选址问题的数学模型,设计了隐枚举法和遗传算法相结合的启发式算法,通过仿真算例验证了方法的可行性和模型的先进性。通过分析得出,在考虑横向调度的情况下,物流系统内总体安全库存和最大虚拟库存总体水平会降低,同时实现对客户的服务承诺也会降低。     

Multi-item partial backlogging inventory models over random planninghorizon in random fuzzy environment

In this paper, some multi-item inventory models for deteriorating items are developed in a random planning horizon under inflation and time value money with space and budget constraints. The proposed models allow stock dependent consumption rate and partially backlogged shortages. Here the time horizon is a random variable with exponential distribution. The inventory parameters other than planning horizon are deterministic in one model and in the other, the deterioration and net value of the money are fuzzy, available budget and space are fuzzy and random fuzzy respectively. Fuzzy and random fuzzy constraints have been defuzzified using possibility and possibility–probability chance constraint techniques. The fuzzy objective function also has been defuzzified using possibility chance constraint against a goal. Both deterministic optimization problems are formulated for maximization of profit and solved using genetic algorithm (GA) and fuzzy simulation based genetic algorithm (FAGA). The models are illustrated with some numerical data. Results for different achievement levels are obtained and sensitivity analysis on expected profit function is also presented.Scope and purposeThe traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However for more sale, inventory should be maintained at a higher level. Of course, this would result in higher holding or procurement cost, etc. Also, in many real situations, during a shortage period, the longer the waiting time is, the smaller the backlogging rate would be. For instance, for fashionable commodities and high-tech products with short product life cycle, the willingness for a customer to wait for backlogging diminishes with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But at present, the economic situation of most of the countries has been much deteriorated due to large scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any further. The purpose of this article is to maximize the expected profit of two inventory control systems in the random planning horizon.     

基于模糊需求的应急物资中心选址—路径问题的算法研究

突发事件爆发后,应急决策通常面临信息不对称的情形,由此获得合理的解决方案非常困难。研究需求量不确定的场景下,同时决策应急物资中心选址方案和配送路径的问题。首先引入三角模糊数刻画模糊需求,提出模糊需求下的应急物资中心选址—路径模型;然后定义Q-学习中的状态、动作和奖励,形成超启发式算法的上层策略;最后以一种新架构封装低层算子,提出一种基于Q-学习的超启发式算法。通过数值实验验证了算法的有效性,同时通过案例分析体现了模型和算法在实际应用中的可行性。     

Multi-objective decision making model under fuzzy random environment and its application to inventory problems

In this paper, we concentrate on developing a fuzzy random multi-objective model about inventory problems. By giving some definitions and discussing some properties of fuzzy random variable, we design a method of solving solution sets of fuzzy random multi-objective programming problems. These are applied to numerical inventory problems in which all inventory costs, purchasing and selling prices in the objectives and constraints are assumed to be fuzzy random variables in nature, and then the impreciseness of fuzzy random variables in the above objectives and constraints are transformed into fuzzy variables which are similar trapezoidal fuzzy numbers. The exact parameters of fuzzy membership function and probability density function can be obtained through fuzzy random simulating the past dates. By comparing the results with those from the fuzzy multi-objective models, we believe that the proposed fuzzy random multi-objective model and hybrid intelligent algorithm provide significant solutions to construct other inventory models with fuzzy random variables in real life.     

A minimax distribution free procedure for mixed inventory model involving variable lead time with fuzzy demand

In a recent paper, Ouyang and Wu applied the minimax decision approach to solve a continuous review mixed inventory model in which the lead time demand distribution information is unknown but the annual demand is fixed and given. However, in the practical situation, the annual demand probably incurs disturbance due to various uncertainties. In this article, we attempt to modify Ouyang and Wu's model by considering two fuzziness of annual demand (i.e., fuzzy number of annual demand and statistic-fuzzy number of annual demand) and to investigate a computing schema for the continuous review inventory model in the fuzzy sense. We give an algorithm procedure to obtain the optimal ordering strategy for each case.Scope and purposeIn most of the early literature dealing with inventory problems, either using deterministic or probabilistic models, lead time is viewed as a prescribed constant or a stochastic variable. Recently, some researchers (e.g., Liao and Shyu, Ben-Daya and Raouf, and Ouyang and Wu) incorporated the crashing lead time idea to continuous review inventory models, in which the annual demand is given and fixed. However, in the real situation, the annual demand will probably have a little disturbance due to various uncertainties. The purpose of this article is to modify the Ouyang and Wu's model to accommodate this reality, specifically, we apply the fuzzy set concepts to deal with the uncertain annual demand. We first consider a case where the annual demand is treated as the triangular fuzzy number. Then, we employ the statistical method to construct a confidence interval for the annual demand, and through it to establish the corresponding fuzzy number (namely, the statistic-fuzzy number). For each fuzzy case, we investigate a computing schema for the new model and develop an algorithm to find the optimal ordering strategy.     

基于横向调度的服务备件物流系统动力学模型与仿真

服务备件物流是一个复杂稳定的系统。从系统动力学的角度分析服务备件物流系统,建立了考虑横向调度和纵向紧急运输情况下,包含一个备件中心仓库和两个备件基层仓库组成的系统动力学模型,检验了其合理性。通过仿真得出以下结论：产品停产期前后,服务备件库存波动加剧,是备件库存管理的敏感期;产品生命周期越短、产品使用年限越长,服务备件库存波动越明显,其库存管理难度越大;各基层仓库服务对象越平均,其协作能力越强,服务备件中心仓库储存库存量越少。     

自适应控制对多级库存延迟问题的优化研究

针对在随机需求下交货延迟所导致供应链多级库存系统库存积压、缺货和牛鞭效应等问题,建立了基于自适应控制算法的多级库存动态优化模型。通过泰勒展开和拉布拉斯变换建立了基于APIOBPCS策略考虑延迟的动态多级库存控制模型;由Lyapunov渐进稳定性定理设计了一种适用于多级库存的模型参考自适应控制算法,其中以无交货延迟的参考库存模型作为目标,通过调节线性补偿函数和自适应控制率,逐渐缩小实际库存模型与参考库存模型间的输出误差,以此削弱交货延迟对多级库存模型的影响;通过实证数据验证了模型参考自适应控制对一个三级供应链库存系统的动态优化效果。仿真结果表明,自适应控制下的无信息共享多级APIOBPCS库存系统缺货全部归零,牛鞭效应下降40.7%。在不增加企业运营投入的前提下,通过自适应控制算法,优化资源配置,动态削弱了交货延迟对多级库存的影响,提升了供应链运营效率。     

模糊随机决策环境下的核电站不常用条件(Q,r)库存模型

针对固定提前期内的需求为三角模糊变量,且用户总需求为梯形模糊随机变量的情形下,构建了不常用备件连续盘点模式下的（Q,r）模型,并推导出模糊成本最小化函数,进而利用基于模糊数期望值理论的去模糊化方法,求出最优订货点及订货量．最后,通过一个实例验证了模型的科学性和实用性．