关于运输问题最优解的进一步讨论

首先给出了运输问题最优解的相关概念,将最优解扩展到广义范畴,提出狭义多重最优解和广义多重最优解的概念及其区别.然后给出了惟一最优解、多重最优解、广义有限多重最优解、广义无限多重最优解的判定定理及其证明过程.最后推导出了狭义有限多重最优解个数下限和广义有限多重最优解个数上限的计算公式,并举例验证了结论的正确性.     

供应中断下具有随机需求的闭环供应链最优差别定价模型

研究了在供应中断下具有随机需求的闭环供应链系统的最优差别定价模型.基于博弈论的理论和方法分别在集中式和分散式决策情形下,确定了最优批发价、最优销售价、最优订购量及系统利润.最后通过数值例子对最优差别定价模型进行了实证分析.     

复合二项对偶模型的最优分红问题

研究复合二项对偶模型的最优分红问题,通过分析HJB方程得到了最优分红策略和相应的最优值函数之间的关系以及最优值函数的简单计算方法.通过讨论最优红利策略的一些性质得到了最优值函数的可无限逼近的上界和下界.     

需求中断下具有提前期的双渠道供应链的风险规避决策

讨论了由一个制造商和一个零售商所组成的双渠道供应链在需求中断下具有提前期的双渠道供应链的风险规避问题.给出了在需求中断前后的最优价格、最优提前期和最优生产决策.研究表明决策变化量是需求中断量的线性函数,在集中式下最优的决策和销售量与供应链的市场份额和需求中断有关,模型的最优生产体现了一定的稳健性.对于提前期来说,当市场份额较大时,最优提前期关于风险规避系数呈正比例,当市场份额较小时,最优提前期关于风险规避系数呈反比例.     

一类随机模型的最优捕获问题研究

在Volterra两种群竞争模型的基础上,构造了随机的具有捕获的两种群竞争模型,研究讨论了捕获对种群生长过程的影响和如何实现最优捕获等问题.从确定性模型入手,深入讨论随机竞争模型的收获最优问题.通过对捕获强度E和贴现率等的估计与讨论,计算出了最优捕获强度最优捕获量最优经济收益.     

竞争与合作统一框架下的鲁棒最优再保险策略

在实际中,多个保险人之间经常存在竞争与合作.文章在竞争与合作统一框架下,研究了鲁棒最优再保险策略.每个保险人的盈余过程满足扩散逼近保险模型,n个保险人的索赔之间存在相依关系,每个保险人通过再保险减少索赔风险.文章主要的研究目标是,在最坏市场环境下,寻找最优均衡再保险策略最大化终端财富的均值同时最小化其方差.通过使用随机动态规划和随机控制理论,求得了鲁棒最优均衡再保险策略、最优市场策略和最优值函数的显式解,并从理论上探讨了最优策略的经济意义.最终,通过数值实验分析了竞争、合作、模糊厌恶和风险厌恶对鲁棒最优均衡再保险策略的影响.文章的研究结果可以有效地指导保险人的实践.     

品牌专营下供应链价格和批量联合最优决策

假定需求是价格的函数,首先研究了非品牌专营下供应链的最优价格决策和最优批量决策,然后研究了品牌专营下供应商、零售商价格和批量的最优决策.建立了供应商优先决策的Stackelberg博弈模型,通过求解得到了该博弈问题均衡解,即得到了供应商控制的品牌产品最优零售价格和零售商控制的最优订货批量.最后将该模型应用于一个实例中,比较了非品牌专营下和品牌专营下最优决策的不同和供应链利润的不同,品牌专营提高了供应链整体的利润以及供应商自身利润占整个供应链利润的比例.     

跳扩散盈余过程的最优投资和最优再保险

站在保险人的立场上,研究了跳扩散盈余过程的最优投资和最优再保险问题.在方差保费原理下,以盈余终值的期望指数效用达到最大作为最优准则,给出了最优策略和值函数的近似表达式.同时也证明了投资总比不投资好的结论.最后,通过一些数例和图表来进一步说明所获得的结论.     

三参数线性规划最优基的稳定性分析

在这篇文章里我们研究一种含三个参数的线性规划最优基的稳定性.得出了最优基的稳定性及二维稳定性的一些较好的结果和最优基稳定的充要条件,并给出了原始、对偶问题的最优解和最优值的级数表达式.避免了计算逆矩阵的巨大工作.文中结果推广了诸如Robert M.FREUND等许多前人的结论.     

多用户多准则随机系统最优与最优收费

针对固定交通需求量和出行者的时间价值为离散分布的多准则随机交通均衡,分别研究了依费用度量和依时间度量的多用户多准则随机系统最优和最优收费问题.分别建立了基于费用和基于时间的随机系统最优的最优化模型,阐述了该模型解的唯一性条件及等价的变分不等式问题.运用变分不等式方法,研究了一阶最优收费的可行性,即能否依边际定价原则,通过收取与出行者类别无关的道路收费使多用户多准则随机均衡流与随机系统最优流一致.一阶最优收费不适用于依时间度量的随机系统最优情况,因而建立了一个最优化模型来得到此时的非歧视性道路收费.最后给出了具体算例.     

带有两货栈及时变需求的变质性物品的最优EOQ模型(英)

本文针对一般的时变需求与两个货栈（自己货栈和租用货栈），建立了变质性物品的最优确定性EOQ模型，提供了用来寻求最优补充策略的方法，并就线性需求出示了两个数值例子．     

Higher order optimization and adaptive numerical solution for optimal control of monodomain equations in cardiac electrophysiology

In this work adaptive and high resolution numerical discretization techniques are demonstrated for solving optimal control of the monodomain equations in cardiac electrophysiology. A monodomain model, which is a well established model for describing the wave propagation of the action potential in the cardiac tissue, will be employed for the numerical experiments. The optimal control problem is considered as a PDE constrained optimization problem. We present an optimal control formulation for the monodomain equations with an extra-cellular current as the control variable which must be determined in such a way that excitations of the transmembrane voltage are damped in an optimal manner.The focus of this work is on the development and implementation of an efficient numerical technique to solve an optimal control problem related to a reaction-diffusions system arising in cardiac electrophysiology. Specifically a Newton-type method for the monodomain model is developed. The numerical treatment is enhanced by using a second order time stepping method and adaptive grid refinement techniques. The numerical results clearly show that super-linear convergence is achieved in practice.     

An optimal replenishment policy for items with inventory-level-dependent demand and fixed lifetime under the LIFO policy

In a recent paper, Hwang and Hahn considered inventory replenishment problems for an item with an inventory-level-dependent demand rate and a fixed lifetime. They developed an EQQ model under the situation of considering the first-in–first-out (FIFO) issuing policy. First, this paper reconsiders Hwang and Hann's problem by employing the last-in–first-out (LIFO) issuing policy, which is more practical in the retail industry. An inventory model is developed. Secondly, the concavity of the objective function is proved. Thirdly, this paper presents conditions where the present model has a unique optimal solution and a method for finding the global optimal solution. A simple solution procedure and sensitivity analyses of parameters are also provided.     

多阶段生产系统最优生产批量和原材料订购决策模型

Sarker和Parija(1996)建立了生产系统最优生产批量和原材料订购决策模型。然而他们的模型仅局限于单阶段生产系统,本文将他们的模型扩展到多阶段生产系统,我们首先建立了使整个多阶段生产系统总成本最小的各阶段最优生产批量、原材料订购批量及阶段之间的运输批量模型,然后分析了原材料订购费、半成品运费及设备安装费的敏感性。最后,我们结合实例综合分析了原材料订购费、半成品运输费和设备安装费的变化及最小值点取整后对原材料订购决策、最优生产批量和总成本的影响。     

An inventory model with backorders with fuzzy parameters and decision variables

The paper considers an inventory model with backorders in a fuzzy situation by employing two types of fuzzy numbers, which are trapezoidal and triangular. A full-fuzzy model is developed where the input parameters and the decision variables are fuzzified. The optimal policy for the developed model is determined using the Kuhn-Tucker conditions after the defuzzification of the cost function with the graded mean integration (GMI) method. Numerical examples and a sensitivity analysis study are provided to highlight the differences between crisp and the fuzzy cases.     

A hybrid heuristic and linear programming approach to multi-product machine scheduling

A new heuristic approach is presented for scheduling economic lots in a multi-product single-machine environment. Given a pre-defined master sequence of product setups, an integer linear programming formulation is developed which finds an optimal subsequence and optimal economic lots. The model takes explicit account of initial inventories, setup times and allows setups to be scheduled at arbitrary epochs in continuous time, rather than restricting setups to a discrete time grid. We approximate the objective function of the model and solve to obtain an optimal capacity feasible schedule for the approximate objective. The approach was tested on a set of randomly generated problems, generating solutions that are on average 2.5% above a lower bound on the optimal cost. We also extend the approach to allow shortages.     

An incremental discount pricing schedule with multiple customers and single price break

This paper analyzes how a supplier can formulate the terms of a quantity discount pricing schedule. Assuming a single incremental discount system, a model is developed from which an algorithm is derived for an optimal discount schedule. The cases are investigated in which both the discount rate and the break point are unknown and either one is prescribed. A numerical example is presented to illustrate the algorithm developed.     

Optimal ordering policies for perishable multi-item under stock-dependent demand and two-level trade credit

In this paper, a multi-item inventory model for perishable items is developed, where the demand rates of the items are stock dependent, two-level trade credit is adopted and the restriction of inventory capacity is also considered. The major objective is to determine the optimal cycle time and order quantities such that the total profit is maximized. The existence and uniqueness of the optimal cycle is discussed by Lagrange approach, and line search algorithms are developed to find the optimal solution of the model. Furthermore, numerical examples are given to illustrate the methods. The sensitivity of the solution to changes in the values of different parameters is also discussed.     

A Gradient Flow Approach to Optimal Model Reduction of Discrete-Time Periodic Systems

This paper is concerned with the optimal model reduction for linear discrete periodic time-varying systems and digital filters. Specifically, for a given stable periodic time-varying model, we shall seek a lower order periodic time-varying model to approximate the original model in an optimal H ₂ norm sense. By orthogonal projections of the original model, we convert the optimal periodic model reduction problem into an unconstrained optimization problem. Two effective algorithms are then developed to solve the optimization problem. The algorithms ensure that the H ₂ cost decreases monotonically and converges to an optimal (local) solution. Numerical examples are given to demonstrate the computational efficiency of the proposed method. The present paper extends the optimal model reduction for linear time invariant systems to linear periodic discrete time-varying systems.     

Markov Decision Processes on Borel Spaces with Total Cost and Random Horizon

This paper deals with Markov Decision Processes (MDPs) on Borel spaces with possibly unbounded costs. The criterion to be optimized is the expected total cost with a random horizon of infinite support. In this paper, it is observed that this performance criterion is equivalent to the expected total discounted cost with an infinite horizon and a varying-time discount factor. Then, the optimal value function and the optimal policy are characterized through some suitable versions of the Dynamic Programming Equation. Moreover, it is proved that the optimal value function of the optimal control problem with a random horizon can be bounded from above by the optimal value function of a discounted optimal control problem with a fixed discount factor. In this case, the discount factor is defined in an adequate way by the parameters introduced for the study of the optimal control problem with a random horizon. To illustrate the theory developed, a version of the Linear-Quadratic model with a random horizon and a Logarithm Consumption-Investment model are presented.