Dynamic Programming and Inventory Control

An expository account is given of the Dynamic Programming approach to inventory analysis in terms of the problem of the optimal storage policy for repair parts. The demand distribution is assumed to be Poisson or some modification thereof; the delivery time is assumed to be fixed or Gamma distributed while preserving the sequence of the orders. No demand is lost. It is shown that the demand distribution for the delivery period is negative binomial. Formulae are derived for the re-ordering point and the order quantity and these are solved for the geometric demand distribution. An example is calculated which is based on the stocking of repair parts by a can manufacturer in Chicago.     

An Application of Dynamic Programming to Pattern Recognition

This paper presents a problem in pattern recognition and formulates it in terms of a dynamic-programming model. Although dynamic programming is usually thought of as an O.R. tool applied to management problems, this paper shows that it has natural applications in pattern matching and recognition, developing aspects of fifth generation computing technology.     

区间值模糊线性规划在证券组合投资优化中的应用

针对期望收益率与风险损失率为区间值模糊数的特征,就证券组合投资问题建立了一种区间值模糊线性规划模型,运用一种对区间值模糊数排序的新算法,将模型转化为经典的线性规划问题进行求解,最后通过一个算例说明其有效性和可靠性,为证券组合投资优化问题的解决提供了一种新的方法,对证券组合的理性投资具有重要的指导意义.     

Convex Quadratic Programming Approach to the Maximum Matching Problem

The problem of determining a maximum matching or whether there exists a perfect matching, is very common in a large variety of applications and as been extensively studied in graph theory. In this paper we start to introduce a characterisation of a family of graphs for which its stability number is determined by convex quadratic programming. The main results connected with the recognition of this family of graphs are also introduced. It follows a necessary and sufficient condition which characterise a graph with a perfect matching and an algorithmic strategy, based on the determination of the stability number of line graphs, by convex quadratic programming, applied to the determination of a perfect matching. A numerical example for the recognition of graphs with a perfect matching is described. Finally, the above algorithmic strategy is extended to the determination of a maximum matching of an arbitrary graph and some related results are presented.     

Convex Quadratic Programming Approach to the Maximum Matching Problem

The problem of determining a maximum matching or whether there exists a perfect matching, is very common in a large variety of applications and as been extensively studied in graph theory. In this paper we start to introduce a characterisation of a family of graphs for which its stability number is determined by convex quadratic programming. The main results connected with the recognition of this family of graphs are also introduced. It follows a necessary and sufficient condition which characterise a graph with a perfect matching and an algorithmic strategy, based on the determination of the stability number of line graphs, by convex quadratic programming, applied to the determination of a perfect matching. A numerical example for the recognition of graphs with a perfect matching is described. Finally, the above algorithmic strategy is extended to the determination of a maximum matching of an arbitrary graph and some related results are presented.     

目标规划在离散型动态投入产出模型中的应用

以离散型动态投入产出模型为约束条件的主体、以决策部门所希望达到的种种目标为约束条件的附加部分,建立动态投入产出目标规划模型.通过求解动态投入产出目标规划模型而得到离散型动态投入产出模型的解.此解法与其它解法相比具有更大的实用价值.     

Robust Process Control by Dynamic Stochastic Programming

Unnecessarily conservative behavior of standard process control techniques can be avoided by stochastic programming models when the distribution of random disturbances is known. In an earlier study we have investigated such an approach for tank level constraints of a distillation process. Here we address techniques that have accelerated the numerical solution of the large and expensive stochastic programs by a factor of six, and then present a refined optimization model for the same application. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Converging Marriage in Honey-Bees Optimization and Application to Stochastic Dynamic Programming

In this paper, we first refine a recently proposed metaheuristic called “Marriage in Honey-Bees Optimization” (MBO) for solving combinatorial optimization problems with some modifications to formally show that MBO converges to the global optimum value. We then adapt MBO into an algorithm called “Honey-Bees Policy Iteration” (HBPI) for solving infinite horizon-discounted cost stochastic dynamic programming problems and show that HBPI also converges to the optimal value.     

The Application of the Negative Binomial Distribution to Stock Control Problems

Random demand and a gamma distribution of lead times results in a negative binomial distribution of the number of demands during a lead time. This fact, together with a rather surprising mathematical equality, enables one to use tables of the positive binomial distribution to determine reorder levels and also to calculate stocks of rotable components for aircraft.     

Dynamic Programming Method for Constrained Discrete-Time Optimal Control

A dynamic programming method is presented for solving constrained, discrete-time, optimal control problems. The method is based on an efficient algorithm for solving the subproblems of sequential quadratic programming. By using an interior-point method to accommodate inequality constraints, a modification of an existing algorithm for equality constrained problems can be used iteratively to solve the subproblems. Two test problems and two application problems are presented. The application examples include a rest-to-rest maneuver of a flexible structure and a constrained brachistochrone problem.     

Maximum Principle for a Stochastic Optimal Control Problem and Application to Portfolio/Consumption Choice

We consider mainly an optimal control problem motivated by a portfolio and consumption choice problem in a financial market where the utility of the investor is assumed to have a given homogeneous form. A Pontryagin local maximum principle is obtained by using classical variational methods. We apply the result to make optimal portfolio and consumption decisions for the problem under consideration. The optimal selection coincides with the one obtained in Refs. 1 and 2, where the Bellman dynamic programming principle was used.     

The Calculation of Order Quantities and Protection Levels in a Re-Order Level Stock Control System

A rapid iterative procedure for calculating order quantities and protection levels is described and attention drawn to an error in a fundamental paper.     

动态规划在教学管理中的应用

本将动态规划理论应用于高校教学管理当中，得出了教学管理中重要的环一排课的最优策略。     

具有最大能量的最短路

本文讨论一类新的赋权图 ,称为双权图 ,G=( V,E;w,c) ,w称为权函数 ,c为容量函数 .并给出了 G中两顶点 u与 v之间具有最大能量的最短路的算法 .