基于JAVA建立树形结构的算法优化

树形结构在程序设计过程具有非常重要的作用,但树形结构的构建相对比较复杂。通过研究设计并实现一种从普通Java对象中建立树形结构的优化算法。     

不可微多目标数学规划的高阶对偶性

引入了一类不可微多目标数学规划的高阶对偶模型。在广义凸性条件下,建立了弱对偶性定理。其结果推广和统一了近期文献上出现的结果。     

灰色参数线性规划解法论

叙述了灰色参数线性规划的基本思想和模型，总结了近十多年来求解的主要研究成果，并对该领域的进一步研究提出了一些想法和展望．     

动态规划确定化学反应器序列最小占用时间的方法

通过用动态规划给出化学反应器序列最小占用时间的设计方法,提出了一个过程的最优化输出设计,该设计在输出产品浓度给定的条件下建立问题的基本设计量和数学模型,利用动态规划原则确定各阶段的占用时间,使总的占用时间为最小值,能够合理的确定各阶段反应器的体积以取得较好的经济效应.图3,表1,参8.     

Generalization of Murty's direct algorithm to linear and convex quadratic programming

Murty's algorithm for the linear complementarity problem is generalized to solve the optimality conditions for linear and convex quadratic programming problems with both equality and inequality constraints. An implementation is suggested which provides both efficiency and tight error control. Numerical experiments as well as field tests in various applications show favorable results.The author thanks K. G. Murty for his encouragement and helpful comments.     

Carathéodory's method for a class of dynamic games

The method of equivalent variational methods, originally due to Carathéodory for free problems in the calculus of variations is extended to investigate feedback Nash equilibria for a class of n-person differential games. Both the finite-horizon and infinite-horizon cases are considered. Examples are given to illustrate the presented results.     

Solving Problems with Min-Type Functions by Disjunctive Programming

We consider applications of disjunctive programming to global optimization and problems with equilibrium constraints. We propose a modification of the algorithm of F. Beaumont for disjunctive programming problems and show its numerical efficiency.     

Sensitivity analysis for discrete optimal control problems

We present local sensitivity analysis for discrete optimal control problems with varying endpoints in the case when the customary regularity of boundary conditions can be violated. We study the behavior of the optimal solutions subject to parametric perturbations of the problem.     

Maximizing a Linear Fractional Function on a Pareto Efficient Frontier

We consider the problem of maximizing a linear fractional function on the Pareto efficient frontier of two other linear fractional functions. We present a finite pivoting-type algorithm that solves the maximization problem while computing simultaneously the efficient frontier. Application to multistage efficiency analysis is discussed. An example demonstrating the computational procedure is included.     

Primal cutting plane algorithms revisited

Dual fractional cutting plane algorithms, in which cutting planes are used to iteratively tighten a linear relaxation of an integer program, are well-known and form the basis of the highly successful branch-and-cut method. It is rather less well-known that various primal cutting plane algorithms were developed in the 1960s, for example by Young. In a primal algorithm, the main role of the cutting planes is to enable a feasible solution to the original problem to be improved. Research on these algorithms has been almost non-existent.  In this paper we argue for a re-examination of these primal methods. We describe a new primal algorithm for pure 0-1 problems based on strong valid inequalities and give some encouraging computational results. Possible extensions to the case of general mixed-integer programs are also discussed.