医药集团物流补货模式创新研究与实证分析——以嘉和嘉事连锁药店为例

医药物流是应用型物流的重要分支,在药品需求随机改变的条件下,配送中心的配送延迟会造成销售的不同步,从而导致配送系统中的各个连锁药店需求点产生滞销或缺货的现象,此时单由医药集团配送中心向各需求点送货并不能保证总成本的最优化。文章针对于医药集团物流补货的原有模式,提出了随机需求条件下集团配送系统的横向补货策略,并在此基础上,分别建立随机库存模型和对应的运输点模型,并结合案例进行了数据模拟,从而实现医药物流集团整体利益的最优化。     

不确定环境下RDC选址问题研究

多配送中心选址问题对整个物流体系的运作和优化起到举足轻重的作用。本文试对不确定环境下配送网络的规划，包括RDC（配送中心）选址和RDC到销售点的配送关系进行研究。构建了确定性规划模型，采用混合遗传算法、应用MATLAB软件给以解决，并进一步结合层次分析法考虑其风险，对初步模型进行优化。结果显示，应用该模型和算法在求解此类问题上具有有效性和实用性，可以满足企业实际决策的需要。     

应急配送网络模型分析——以天气随机变化为考虑因素

应急配送网络构建主要研究趋势为不确定性的模型,而其中的不确定性较少考虑天气状况。本文通过五个部分介绍了考虑天气随机变化的应急配送网络构建的意义、描述、基本假设、模型和求解步骤,具有一定的实际意义和学术价值。     

带软时间窗的冷链物流配送路径优化研究

消费者对生鲜产品的需求不断增加,促进了城市冷链物流的快速发展。文章分析了冷链车的能耗成本和货损成本,并将运输过程和卸货过程分开进行考虑,以总成本最低为目标建立了带软时间窗的优化模型。针对具体模型特点设计遗传算法进行求解,最后结合具体实例进行仿真试验,遗传算法所得配送线路方案比原有扫描法配送方案成本明显更低,从而验证了模型和算法的有效性。     

考虑碳排放和时间约束的O2O零售企业配送中心选址优化

近年来,随着电子商务的持续增长、城市环境可持续发展能力要求不断提升,优化城市配送中心选址迫在眉睫。因此,文章引入碳排放、时间约束等2个因素到O2O零售企业配送中心选址问题中,考虑到O2O零售企业线上线下订单需求难以预测,运用随机规划理论,构建以总成本最小为目标,不确定性需求为随机约束的选址模型,并利用Lingo软件进行求解,最终得到O2O零售企业配送中心的选址方案,从而实现降低配送成本、缓解配送业务给城市环境带来的压力等目标。     

成品油终端配送预测模型研究与应用

以一个成品油配送局部系统为研究基础,建立预测模型,模拟预测下一日需求量和下一日配车需求,为成品油销售系统实现主动配送提供了模型研究基础和实际应用例示。     

基于最优路线选址的遗传算法程序设计与实现

一、基于最优路线的配送中心选址模型 1.建立曩优路线选址模型的条件假设 (1)仅在一定被选范围内考虑新的配送中心设置;(2)配送区域内各需求点数量已知,地点确定;(3)该配送区域内只允许设一个配送中心,负责对所有需求点提供配送服务:(4)连接各需求点之间道路长度和通行方向已知,由于假定运输费用与道路长度成正比,所以道路的长度可直接看成经过该道路的运输费用:(5)每条配送路径上各需求点的需求量之和不超过汽车的载重量:(6)每条配送路径的长度不超过汽车一次配送的最大行驶距离.     

应急物资配送网络构建研究

突发事件背景下,配送网络设计的科学性对应急物资供应的及时性有很大影响。目前研究较多的供应点直达需求点的供应网络对重大突发事件的应急救援活动的支撑,存在较多局限性。因此本文提出面向重大突发事件,构建三级供应网络的必要性,并以三级供应网络的构建问题为研究对象,将物资分配与中转站选择综合考虑,以便统筹全局,更加科学地制定方案。建立了需求模糊条件下,以单位物资运输时间最小和中转站数量最少为目标的多物资多目标优化模型。采用平均权重法处理模糊约束,通过ε约束法处理多目标,并使用Lingo软件编程实现算法。仿真实例表明提出模型和算法的有效性,从而为决策者制订分配方案和配送网络选址方案提供科学决策支撑。     

电商物流末端配送网络多目标优化模型设计

尽管近年来物流配送速度已有大幅提升,但在一些特殊节假日如"双十一",配送的及时性仍不能得到满足,交货延迟、节点货物堆积甚至"爆仓"等情况时有发生,直接影响消费者对电商服务的质量评价。在分析国内外电商物流末端配送网络研究现状的前提下,根据电商物流配送网络理论、多目标优化理论以及网络抗毁性理论,展开对电商物流末端配送网络的分析,确定了网络抗毁性和经济成本对网络优化的影响,分析了网络经济成本的组成与网络抗毁性的来源以及测量标准。在此基础上,采用多目标优化,对电商物流末端配送网络进行优化,分别构建经济成本最小与网络抗毁性最高的优化模型,判定两者对电商物流末端配送网络优化的影响情况,结论显示,引入抗毁性这一优化目标更能对电商物流配送网络优化的合理性,保障其稳定性。仿真分析也验证了此结论,基于理论和现状的分析,以及仿真实验的结果,提出了电商物流末端配送网络优化的合理方案。     

浅谈多目标优化决策方法

随着科学技术的不断进步,传统的只考虑单一目标的方法已经不能满足人们的需求,在进行决策的过程中,对多目标问题进行综合的考虑,并用合理的优化方法对其进行决策将会带来很大的实际效益。     

Capital Accumulation in a Stochastic Overlapping Generations Model with Social Security

This paper analyzes the impact of pay-as-you-go financed social security on the stochastic process for the capital stock in a stochastic overlapping generations model. It is shown that the probability distribution of the capital stock in absence of social security dominates that in a pay-as-you-go system in the sense of stochastic dominance. Furthermore, the study demonstrates that the sufficient conditions ensuring the existence and uniqueness of stationary equilibria in a pay-as-you-go system are more restrictive than in the model without social security. Journal of Economic Literature Classification Numbers: C62, H55.     

A Q-theory model with lumpy investment

We present an analytically tractable dynamic stochastic general equilibrium model that incorporates micro-level fixed and convex adjustment costs. We provide an explicit characterization of equilibrium dynamics by a system of nonlinear stochastic difference equations. We provide general conditions under which our model features investment lumpiness at the microeconomic level, but aggregate dynamics are isomorphic to those in a Q-theory model without fixed costs. This theoretical result is independent of the specification of the fixed cost distribution and also holds true when firms face persistent idiosyncratic productivity shocks.     

Resource allocation in a general equilibrium model of production under uncertainty

The purpose of this paper is to examine the implications of uncertainty for resource allocation, real income, and income distribution in terms of a simple two-sector general equilibrium model of a small country where uncertainty is introduced by assuming that production in one sector occurs in a stochastic environment. Assuming decreasing risk aversion, we show that an increase in uncertainty causes the movement of the resources away from the uncertain sector, a decline in expected real income, and a shift in the distribution of income against the factor employed intensively by the uncertain sector.     

The Microeconomics of an R&D-Based Model of Endogenous Growth

This paper explores the microeconomic structure underlying a class of endogenous growth models in which product differentiation and stochastic quality growth coexist. The general equilibrium model generates a stationary stochastic equilibrium in which a nondegenerate ergodic distribution of firm size depends systematically on parameters of the model. Features of the model necessary for stable endogenous aggregate growth are explored, and predictions of the model are compared with microeconometric evidence on R&D intensity, firm growth, and concentration.     

Learning,large deviations and rare events

We examine the role of generalized stochastic gradient constant gain (SGCG) learning in generating large deviations of an endogenous variable from its rational expectations value. We show analytically that these large deviations can occur with a frequency associated with a fat-tailed distribution even though the model is driven by thin-tailed exogenous stochastic processes. We characterize these large deviations, driven by sequences of consistently low or consistently high shocks and then apply our model to the canonical asset pricing framework. We demonstrate that the tails of the stationary distribution of the price–dividend ratio will follow a power law.     

Stability and bifurcation in a simple heterogeneous asset pricing model

Stability and bifurcation analysis of deterministic systems has been widely used in modeling financial markets. We develop a simple pricing model with two types of rational traders, fundamentalists and chartists, in order to study well price behavior in financial markets, we use student t distribution to replace traditional normal distribution to describe fundamental price process. We study the stability and bifurcation of the underling deterministic system and use numerical simulation to study the dynamic of the stochastic system, including autocorrelations structures and high kurtosis of the returns. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced).     

Optimal stationary consumption with stochastic production and resources

Uncertainty about technology and resources is represented in terms of uncertainty about an (exogenous) environment whose successive states form a stationary stochastic process, with probabilities that are unaffected by economic decisions. The successive states of the economy depend both on the environment and on the decisions taken with regard to production and consumption. It is shown that, under conditions that are natural extensions of “neoclassical” conditions in the case of certainty, (1) Capital saturation is possible, i.e., an optimal stationary stochastic program exists, and (2) An optimal program can be sustained by a price system that takes the form of a stationary stochastic process of price vectors. In other words, an optimal stationary program can be sustained by a stochastic “equilibrium,” in which at each date the optimal production decisions maximize expected intertemporal profit, and the optimal aggregate consumption vector has minimum cost among all aggregate consumption vectors yielding no less (social) utility.     

The effect of feedback consistency on success in markets with positive feedbacks

In this paper, we show how the finite time expected outcomes in a stochastic ball and urn model depend on the variation in feedbacks by applying the concept of second order stochastic dominance to the feedback distribution. We find that less variation leads to greater expected outcomes.     

A TWO FACTOR MODEL OF INCOME DISTRIBUTION DYNAMICS

This paper analyzes empirical income distributions and proposes a simple stochastic model to explain the stationary distribution and deviations from it. Using the individual tax returns data in the U.S. and Japan for 40 years, we first summarize the shape of the income distribution by an exponential decay up to about the 90th percentile and a power decay for the top 1 percent. We then propose a minimal stochastic process of labor and asset income to reproduce the empirical characteristics. In particular, the Pareto exponent is derived analytically and matched with empirical statistics.