Optimization of component reliability in the design phase of capital goods

We introduce a quantitative model to support the decision on the reliability level of a critical component during its design. We consider an OEM who is responsible for the availability of its systems in the field through service contracts. Upon a failure of a critical part in a system during the exploitation phase, the failed part is replaced by a ready-for-use part from a spare parts inventory. In an out-of-stock situation, a costly emergency procedure is applied. The reliability levels and spare parts inventory levels of the critical components are the two main factors that determine the downtime and corresponding costs of the systems. These two levels are decision variables in our model. We formulate the portions of Life Cycle Costs (LCC) which are affected by a component’s reliability and its spare parts inventory level. These costs consist of design costs, production costs, and maintenance and downtime costs in the exploitation phase. We conduct exact analysis and provide an efficient optimization algorithm. We provide managerial insights through a numerical experiment which is based on real-life data.     

Evaluating the effects of distribution centres on the performance of vendor-managed inventory systems

This paper evaluates the effects of the distribution centre (DC) in a vendor-managed inventory (VMI) system comprising one manufacturer, one DC and n retailers. Adopting the order-up-to-level (OUL) replenishment policy, the system aims to maximize the overall system profit. We propose a model to evaluate the system performance by considering the scale of the distribution network, influential cost factors, demand distribution, planning horizon, and facility locations. From the viewpoint of a supply chain, we examine the DC’s effects on the system in terms of net profit. Our findings reveal that the DC has effects on demand variance and system profit, and there are some dominant factors that affect the overall system performance. The DC may lead to different system performance under a variety of cost factors, and in some situations, the DC may negatively affect system performance. We also suggest some innovative uses of the DC’s location to help enhance system performance.     

Managing an integrated production inventory system with information on the production and demand status and multiple non-unitary demand classes

In this paper, we study a system consisting of a manufacturer or supplier serving several retailers or clients. The manufacturer produces a standard product in a make-to-stock fashion in anticipation of orders emanating from n retailers with different contractual agreements hence ranked/prioritized according to their importance. Orders from the retailers are non-unitary and have sizes that follow a discrete distribution. The total production time is assumed to follow a k₀-Erlang distribution. Order inter-arrival time for class l demand is assumed to follow a k_l-Erlang distribution. Work-in-process as well as the finished product incur a, per unit per unit of time, carrying cost. Unsatisfied units from an order from a particular demand class are assumed lost and incur a class specific lost sale cost. The objective is to determine the optimal production and inventory allocation policies so as to minimize the expected total (discounted or average) cost. We formulate the problem as a Markov decision process and show that the optimal production policy is of the base-stock type with base-stock levels non-decreasing in the demand stages. We also show that the optimal inventory allocation policy is a rationing policy with rationing levels non-decreasing in the demand stages. We also study several important special cases and provide, through numerical experiments, managerial insights including the effect of the different sources of variability on the operating cost and the benefits of such contracts as Vendor Managed Inventory or Collaborative Planning, Forecasting, and Replenishment. Also, we show that a heuristic that ignores the dependence of the base-stock and rationing levels on the demands stages can perform very poorly compared to the optimal policy.     

基于系统动力学的供应链库存策略仿真研究

针对一个动态、多级的供应链库存系统,应用系统动力学的方法,建立了供应链(s,S)库存策略下的物流成本模型,并通过动态仿真,分析了库存策略的变动对于供应链库存系统各级成员间库存供需的动态行为,提出了(s,S)策略下的供应链库存系统的有效管理方法.     

基于信用额度和外生违约概率的出口海陆仓融资质押率优化

质押率优化是出口海陆仓融资决策的核心内容。针对出口商信用、出口商与进口商外生违约以及质押物价值波动三重叠加风险下的出口海陆仓融资决策问题,在设定出口商信用额度,且给定出口商和进口商外生违约概率的前提下,依据双重Stackelberg博弈原理,以供应链协同均衡下的出口商、进口商和船公司的期望利润最大化为目标,建立了质押率与订货量及货物价格联动优化模型,设计了微分法和逆向归纳法求解模型。算例验证了模型和方法的适用性和有效性。敏感性分析结果表明质押率与出口商信用额度呈负相关关系,对出口商和进口商外生违约概率不敏感。研究结论可为出口海陆仓融资优化决策提供科学参考。     

基于零售商过度自信的存货质押博弈决策模型

存货质押是中小企业短期融资的有效手段,而企业对需求的过度自信会影响融资企业和银行的决策,从而影响到企业和银行的预期收益。针对过度自信环境下的存货质押决策问题,建立过度自信零售商和银行的存货质押博弈决策模型,采用Stackelberg博弈分析期望需求和需求波动性两方面过度自信对零售商销售努力、订货量和银行质押率的影响。研究表明:过度自信零售商融资更为激进,过度自信程度越高,对资金需求越大,投入销售努力越高,采购量越大,预期利润与实际利润之间的偏差越大;在低利润市场环境下,质押率随着过度自信的增加而降低,在高利润市场环境下,质押率会随着预测精度过度自信的增加而增加,随着期望需求过度自信的增加而下降。     

需求依赖价格下港口存货质押业务中质押率研究

港口与银行合作办理质押贷款业务,不仅能增加港口的存储收入和金融收入,同时也能吸引更多的客户,从而增加其主营业务收入。在银行统一授信港口情况下,本文分析了质押物品的需求依赖价格条件下,风险中性的港口质押贷款业务中的最优质押率计算方法。并分别分析了在乘积型和加型随机需求函数条件下,质押产品价格、企业违约概率和质押物品数量以及质押期限对最优质押率和港口最大期望收益的影响,并通过数值分析验证了所有结论。     

一类跳扩散需求存贮系统(s,S)库存控制策略研究

考虑的是连续检查库存,需求为一个常时间函数和-个复合Poison跳扩散随机过程的和的存贮系统最优库存控制问题.基于期望折扣成本最小建立了无穷时间区间具有固定订购成本的最优库存模型,确定可采用(s,S)策略进行库存控制,给出了最优(s,S)策略的充要条件--HJB方程Ⅰ、Ⅱ.我们采用"猜测"的方法确定了最优(s,S)策略对应的值函数形式,建立了确定库存参数的最优化模型.     

Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem

Simulation optimization has received considerable attention from both simulation researchers and practitioners. In this study, we develop a solution framework which integrates multi-objective evolutionary algorithm (MOEA) with multi-objective computing budget allocation (MOCBA) method for the multi-objective simulation optimization problem. We apply it on a multi-objective aircraft spare parts allocation problem to find a set of non-dominated solutions. The problem has three features: huge search space, multi-objective, and high variability. To address these difficulties, the solution framework employs simulation to estimate the performance, MOEA to search for the more promising designs, and MOCBA algorithm to identify the non-dominated designs and efficiently allocate the simulation budget. Some computational experiments are carried out to test the effectiveness and performance of the proposed solution framework.     

VMI条件下具有复合二项随机需求的销售商库存策略研究

考虑一个典型的单一产品的二级供应链系统:单供应商对单销售商,假定系统中销售商的需求分布为复合二项分布,未满足的需求机会损失;补货间隔时间为一随机变量.本文采用概率方法对销售商的需求分布、期望缺货、期望库存周期及库存的稳定性分布进行研究的基础上,构建了使单位时间内销售商的期望库存成本费用最小的库存模型,由此模型便可确定VMI模式下供应商对销售商的库存补货参数s和S,并且给出了在补货响应时间为泊松分布的情况下模型的求解算法,还给出了及时补货响应情况下的5个算例.为补货策略的实施提供了一种简单易于控制的思路和方法.