基于模糊集的经济订货批量模型的优化研究

本文对模糊环境下的库存问题进行了研究,采用梯形模糊数来描述现实生产环境,对不允许缺货、全部要素均为模糊数时的经济订货批量模型进行优化求解.数据分析表明,虽然实际环境是模糊的,但是最优决策是确定的.当所有生产要素均为常数时,模糊库存模型可以退化为确定性条件下的经济订货批量模型.并对模糊集范围对经济订货批量和年库存总成本函数的影响进行了数据分析和仿真.     

大连可持续发展模型的构建

可持续发展系统中包括社会,经济、能源以及环境四个子系统,本文选取大连可持续发展系统中社会、经济、能源环境四个子系统中的相关数据,建立社会模型组、经济模型组以及能源与环境模型组。其中社会模型组主要包括与人口相关的社会需求模型;经济模型包括经济增长模型,财政收入模型;能源与环境模型包括能耗模型和污染物排放量模型。     

基于期权视角的海外市场拓展的双目标多项目多期优化随机机会约束模型

随着经济全球化趋势进程的加快,海外市场资源优化配置逐步成为理论研究和实务关注的热点,而已有研究却鲜有涉及海外目标市场开拓的资源配置问题。本文在对此问题进行分析的基础上,提出了基于期权度量的收益目标模型和基于信息熵度量的风险目标模型,构建了随机环境下基于现金流供需约束的双目标多项目多期优化0-1机会约束优化模型。在吸取NSGA-Ⅱ算法思想的基础上对DE算法进行了改进,设计了求解此类配置问题的Pareto解算法,比较了伸缩因子分别为固定数和随机数时差分算法的性能,得出后者算法性能稍微优于前者。     

基于霍尔三维结构的地方政府优化发展环境评价体系研究

在我国地方经济的快速发展历史进程中,投资起到了巨大的推动作用,如何营造优质的投资环境并合理评价发展环境优化程度借以吸引更多资金和项目成为各级地方政府工作的重点.本文基于霍尔三维结构理论,结合我国地方政府优化发展环境评价工作是一项结构复杂,涉及因素众多的系统工程的实情,从逻辑维、时间维和知识维3方面构建地方政府发展环境优化评价体系,促进地方经济又好又快发展.     

Excel在存货管理决策中的应用

经济订货量法是现代库存优化的方法之一.本文以Excel为工具,分别就库存管理决策基本的经济订货批量模型、扩展的经济订货批量模型和有数量折扣不允许缺货的经济订货模型进行了分析设计.透过实例表明,这些模型简单、实用,可以作为存货管理决策的有效工具.     

共享“精品”——精品 我们共同的追求

经济订货量法是现代库存优化的方法之一。本文以Excel为工具,分别就库存管理决策基本的经济订货批量模型、扩展的经济订货批量模型和有数量折扣不允许缺货的经济订货模型进行了分析设计。透过实例表明,这些模型简单、实用,可以作为存货管理决策的有效工具。     

ANP驱动的移动增值战略匹配定性模拟及优化

服务商增值战略匹配已超出单一企业的范畴,有必要进行基于价值链环境的跨企业决策。为实现基于价值链环境的增值战略匹配,以价值链均衡为优化目标,建立受当前决策变量状态约束的优化模型。针对信息不完全条件下的动态多目标优化问题,提出实证关系驱动的定性模拟进行求解。扩展传统战略匹配模型(SAM)至信息不完全的价值链环境中,抽象出优化模型描述。以增值战略匹配为研究对象,设计了问卷,利用ANP方法获取决策变量之间的关系。通过QSIM算法驱动因素间交互关系的动态演化,确定实现价值链增值战略均衡时的最佳决策变量组合。算例分析表明了该模型和算法的有效性,能为移动增值战略的实时优化决策提供支持。根据计算结果可以确定战略要素的发展优先级,从而实现资源的优化配置。     

考虑长期运力合同的班轮收益管理运输路径优化模型

基于收益管理的方法,文章对随机需求环境下班轮运力分配和路径优化问题进行了定量研究。首先针对海运收益管理的特征,建立了考虑长期运力合同、空箱调运的轮运力分配和路径选择随机规划模型,然后应用稳健优化方法对此模型进行求解。最后,通过数值仿真得到了优化的舱位分配方案,比较发现稳健优化模型取得了较确定性规划模型更好的收益,显示了模型和方法对于集装箱海运企业的收益管理问题具有应用价值。     

基于改进粒子群优化方法的供应商优选与订货量分配模型

研究了随机性需求环境下的供应商优选与订货量分配问题,构建了以质量、成本、交货期3个准则为目标函数、以其他目标为约束条件的多目标随机约束规划模型;借助于加权法和罚函数法,将多目标随机约束规划模型转化为单目标优化模型;进而设计了带惯性因子和收缩因子的粒子群优化求解算法对所建模型进行求解,并与常用的遗传算法求解方法进行对比分析,实例验证了粒子群优化算法解决此类优化问题的可行性和有效性.     

招商引资的“方程式”

要想强县必须发展工业，要发展工业必须有项目，要有项目必须招商引资，要招商引资必须优化环境，而要优化环境必须实干，这是县域经济发展的内在逻辑。     

Optimal Acquisition of FMS Technology Subject to Technological Progress*

In order to gain competitive advantage, a firm must link its technology choice to its total manufacturing strategy and business unit's goals. A dynamic model is presented to examine the strategic decision concerning the acquisition of flexible manufacturing systems (FMS) technology. A major contribution of this model is its ability to capture the strategic benefits of FMS with respect to economies of scope and technological progress. Decisions such as the timing and size of new technology acquisition and the scrapping of conventional capacity are explored as a firm plans for the upgrading of its facility to meet future dynamic strategic goals. This model may be used to assist with strategic planning because it identifies the critical relationships and trade-offs between various exogenous forces (such as market growth or decay, the cost of acquiring flexible manufacturing systems, and the rate of technological progress) and the decision variables considered.     

Distributed Computer System Capacity Planning and Capacity Loading

The availability of micro-, mini-, and super computers has complicated the laws governing the economies of scale in computers and has increased the tendency to decentralize and distribute computing power. The optimal design of such a system requires integration of computers of varying power and a strategy for capacity loading. This paper considers the problem of capacity planning and capacity loading of a distributed computer system as a hierarchy of decisions. A linear programming model is developed for the initial capacity planning problem. A loading model that accounts for variations in arrival and processing rates of the jobs in a dynamic environment is developed to support the operations.     

Optimal inventory model for items with imperfect quality and shortage backordering

In this study, we develop an optimal inventory model for items with imperfect quality and shortage backordering. Such implicit assumption is reasonable in view of the fact that poor-quality items do exist during production. They are usually picked up during the screening process and are withdrawn from stock instantaneously. It is assumed that all customers are willing to wait for new supply when there is a shortage. The analysis shows that our model is a generalization of the models in current literatures. An algorithm and numerical analysis developed show that our model always results in better performance.     

Optimal Stopping With Multiple Priors

We develop a theory of optimal stopping under Knightian uncertainty. A suitable martingale theory for multiple priors is derived that extends the classical dynamic programming or Snell envelope approach to multiple priors. We relate the multiple prior theory to the classical setup via a minimax theorem. In a multiple prior version of the classical model of independent and identically distributed random variables, we discuss several examples from microeconomics, operation research, and finance. For monotone payoffs, the worst‐case prior can be identified quite easily with the help of stochastic dominance arguments. For more complex payoff structures like barrier options, model ambiguity leads to stochastic changes in the worst‐case beliefs.     

A Theory of Optimal Inheritance Taxation

This paper derives optimal inheritance tax formulas that capture the key equity‐efficiency trade‐off, are expressed in terms of estimable sufficient statistics, and are robust to the underlying structure of preferences. We consider dynamic stochastic models with general and heterogeneous bequest tastes and labor productivities. We limit ourselves to simple but realistic linear or two‐bracket tax structures to obtain tractable formulas. We show that long‐run optimal inheritance tax rates can always be expressed in terms of aggregate earnings and bequest elasticities with respect to tax rates, distributional parameters, and social preferences for redistribution. Those results carry over with tractable modifications to (a) the case with social discounting (instead of steady‐state welfare maximization), (b) the case with partly accidental bequests, (c) the standard Barro–Becker dynastic model. The optimal tax rate is positive and quantitatively large if the elasticity of bequests to the tax rate is low, bequest concentration is high, and society cares mostly about those receiving little inheritance. We propose a calibration using micro‐data for France and the United States. We find that, for realistic parameters, the optimal inheritance tax rate might be as large as 50%–60%—or even higher for top bequests, in line with historical experience.     

Optimal knowledge outsourcing model

Every organization controls its investments in the development and maintenance of internal knowledge (IK) as opposed to outsourcing this effort, namely, consuming external knowledge (EK). A number of factors involved in this decision, such as the IK learning curve, its associated holding cost, value deterioration rate, value of future IK or cost of purchasing EK. This study proposes a dynamic optimal control model for examining the properties of this problem. Optimal control strategies and steady-state conditions are identified for a number of special cases. Some insightful observations are obtained by studying the solution sensitivity to the underlying assumptions.     

零售商主导下促进绿色产品需求的联合研发契约协调研究

针对绿色环保产品价格过高,阻碍其成为主流消费品这一现实问题,在绿色经济背景下,探讨零售商向负责绿色研发成本投入的制造商提供不同联合研发契约时的供应链均衡策略和协调问题。以零售商主导的双边垄断型绿色供应链为研究对象,在考虑消费者环保意识、产品绿色度水平、价格等多种因素影响需求的基础上,分别探讨批发价契约、成本分担契约和两部制契约对绿色产品需求、供应链成员利润及渠道利润的影响。结果表明,成本分担契约无法实现供应链成员利润的Pareta改进;一定条件下,两部制契约可以实现供应链成员利润的双赢,并提高绿色产品的市场需求。此外,虽然消费者环保意识的提高并不总是会带来绿色产品市场需求的增加,但却总是会使得绿色供应链的利润提高;并且较高的消费者环保意识将激励企业追求一个较低的绿色成本系数,从而促使企业积极进行绿色技术创新努力。     

Optimum Conservative Price Increase Decisions in a Competitive Market

This paper outlines a systematic procedure for a firm's price increase decisions in a competitive market. Following a conservative approach, a previously published competitive pricing model is extended and used to address the question of where, when, and by how much prices should be raised. In its present form, the approach is useful for low priced, frequently purchased products.     

Optimal dispatching control of an AGV in a JIT production system

This paper deals with an FMS (Flexible Manufacturing System) in a JIT (Just-In-Time) production system. The FMS consists of m workstations, one dispatching station and a single AGV (Automated Guided Vehicle). Each workstation has an input buffer of limited capacity and its processing times are distributed stochastically. When the processing of a new component starts at the workstation, a withdrawal Kanban attached to it is sent to the dispatching station. The AGV chooses one from workstations whose withdrawal Kanbans are accumulated at the dispatching station, and conveys a component with a withdrawal Kanban from the dispatching station to the workstation. The main purpose of this paper is to find an optimal dispatching policy of the AGV that maximizes the long-run expected average reward per unit time. The problem is formulated as a semi-Markov decision process and an optimal dispatching policy is computed. Numerical experiments are performed to make several comparisons.     

Optimal Strategies for Traditional versus Roth IRA/401(k) Consumption During Retirement

We establish an algorithm that produces an optimal strategy for retirees to withdraw funds between their tax‐deferred accounts (TDAs), like traditional IRA/401(k) accounts, and their Roth IRA/401(k) accounts, in the context of a financial model based on American tax law. This optimal strategy follows a geometrically simple, intuitive approach that can be used to maximize the size of a retiree's bequest to an heir or, alternatively, to maximize a retiree's portfolio longevity. We give examples where retirees following the approach currently implemented by major investment firms, like Fidelity and Vanguard, will reduce their bequests by approximately 10% or lose 18 months of portfolio longevity compared to our optimal approach. Further, our strategy and algorithm can be extended to many cases where the retiree has additional, known yearly sources of money, such as income from part‐time work, taxable investment accounts, and Social Security.