利润最大问题与弱DEA有效(C2GS2)

对利润最大问题[1]本文用不同于文[1]的方法来讨论.通过解这一个问题,不但知道在一定条件下有最大利润的决策单元的弱DEA有效性(C2GS2),而且找到所有有最大利润的决策单元.     

Exact approaches for testing non-inferiority or superiority of two incidence rates

We studied an unconditional approach based on partial maximization using different penalty values for comparing two incidence rates from Poisson distributions. We also consider a full maximization approach and an approach based on estimation and full maximization. Generally, the third approach has good performance.     

Complete mixed integer linear programming formulations for modularity density based clustering

Modularity density maximization is a clustering method that improves some issues of the commonly used modularity maximization approach. Recently, some Mixed-Integer Linear Programming (MILP) reformulations have been proposed in the literature for the modularity density maximization problem, but they require as input the solution of a set of auxiliary binary Non-Linear Programs (NLPs). These can become computationally challenging when the size of the instances grows. In this paper we propose and compare some explicit MILP reformulations of these auxiliary binary NLPs, so that the modularity density maximization problem can be completely expressed as MILP. The resolution time is reduced by a factor up to two order of magnitude with respect to the one obtained with the binary NLPs.     

信息熵增量最小化准则在供应链中的应用

本文研究了在考虑利润最大化准则和信息熵增量最小准则下，既能满足了利润最大化，又要增加利润可得性，销售商如何确定订购量的问题。数字实验表明：考虑双重准则得到的策略比仅考虑利润最大化准则得到的策略更好，可以使供应链、销售商及制造商都受益。     

基于主客观信息综合判断的非线性拉开档次法

针对以最大程度的拉开被评价对象间差异的综合评价问题,通过分析线性拉开档次法存在的局限性,本文提出了一种基于主客观信息综合判断的非线性拉开档次法,旨在进一步丰富和完善拉开档次法的理论知识。首先对线性拉开档次法进行简单的介绍,并分析了线性拉开档次法的局限性;然后提出前提假设,给出非线性因子选取的原则以及确定指标序关系的方法,并给出排序后相邻指标重要程度比值的选取方法,根据评价原则利用规划模型求解各评价指标的权重系数,利用求得的指标权重采用非线性集结模型计算最终的评价结果;最后用一个算例验证了方法的有效性。     

An existence result for maximizations with respect to cones

A sufficient condition is given for the existence of a solution to a generalized Pareto maximization problem in which maximization is defined in terms of cones. This result generalizes the fact that an upper semicontinuous real-valued function achieves its maximum on a compact set.     

基于子空间多核学习的企业财务困境预测方法

财务指标的异构性是影响企业财务困境预测精度的重要因素,现有多核学习方法能够用于解决异构数据学习问题。本文首先介绍了子空间多核学习财务困境预测理论框架,在此基础上根据子空间学习的最大化方差准则、类别可分性最大化准则、非线性子空间映射原理,提出了三种子空间多核学习方法,分别为最大化方差投影子空间多核学习、类别可分性最大化子空间多核学习、非线性子空间多核学习。利用采集的我国上市公司数据进行实验,对比所提出的方法同现有代表性财务困境预测方法,并对实验结果进行分析。实验结果表明,本文提出的子空间多核学习财务困境预测框架行之有效,该框架下所构造的子空间多核学习预测方法能够有效地提升财务困境预测精度。     

Generalized Newton method for linear optimization problems with inequality constraints

A dual problem of linear programming is reduced to the unconstrained maximization of a concave piecewise quadratic function for sufficiently large values of a certain parameter. An estimate is given for the threshold value of the parameter starting from which the projection of a given point to the set of solutions of the dual linear programming problem in dual and auxiliary variables is easily found by means of a single solution of the unconstrained maximization problem. The unconstrained maximization is carried out by the generalized Newton method, which is globally convergent in an a finite number of steps. The results of numerical experiments are presented for randomly generated large-scale linear programming problems.     

Efficiency and proper efficiency in vector maximization with respect to cones

Vector maximization problems arise when more than one objective function is to be maximized over a given feasibility region. The concepts of efficiency and proper efficiency have played a useful role in the analysis of such problems. Recently these concepts have been extended to vector maximization problems in which the underlying domination cone is a convex cone. In this paper, efficient and properly efficient solutions for the vector maximization problem in which the underlying domination cone is any nontrivial, closed convex cone are examined. Differences between properly and improperly efficient solutions are established. Characterizations of efficient and properly efficient solutions are presented, and conditions under which efficient solutions exist and fail to exist are derived.     

基于社会福利最大化的油气资源税费研究

合理的油气资源税费能够引导企业优化开发决策,平衡当代与后代利益关系,实现跨期资源有效配置。从跨期油气资源最优分配的角度,通过最优控制理论构建寡头垄断市场中社会福利最大化和企业利润最大化目标下的油气资源开发决策模型,并以社会福利最大化目标下的资源开发决策为基准,研究从价、从量、储量三种不同形式的油气资源税费对资源开发决策的调节作用,研究发现:(1)征收从价税费,最优的从价税率为26.4%,政府既可以保障社会最优,还可以获得较多的税费收入;(2)征收从量税费,从量税率为1.77元/吨,政府可以保证社会福利最大化,但相比从价税费政府的税费收入较少;(3)征收储量税费,社会福利最大化下的储量税费为-0.13元/吨,也就是政府需向企业进行补贴才可以保证社会最优,会形成一定的财政压力。     

Continuous optimization problems and a polynomial hierarchy of real functions

The close connection between the maximization operation and nondeterministic computation has been observed in many different forms. We examine this relationship on real functions and give a characterization of NP-time computable real functions by the maximization operation. A natural extension of NP-time computable real functions to a polynomial hierarchy of real functions has a characterization by alternating operations of maximization and minimization. Although syntactically this hierarchy of real functions can be treated as a polynomial hierarchy of operators, the well-known Baker-Gill-Solovay separation result does not apply to this hierarchy. This phenomenon is explained by the inherent structural properties of real functions, and is compared with recent studies on positive relativization.     

Wholesale pricing and evolutionarily stable strategies of retailers with imperfectly observable objective

This paper develops a one-population (indirect) evolutionary game model of a supply chain with one manufacturer/supplier and many (a sufficiently large number of) retailers to study how the retailer’s marketing objective depends on the wholesale price, its observability, the error probability of the observed result on the rival’s preference, the market scale and the retailer’s bargaining power. This paper also presents an algorithm for computing the optimal wholesale price of the manufacturer. We find that the profit (revenue) maximization behavior is an evolutionarily stable marketing strategy if the wholesale price is sufficiently high (low). Given an appropriate wholesale price, the revenue maximization behavior coexists with the profit maximization behavior in the retailers’ population. The larger the market scale, the stronger the motivation of the retailer to take profit maximization behavior due to a higher wholesale price. The cross effects of the retailer’s reservation payoff and the other factors should be considered in the decision process.     

Piecewise convex formulations of binary and permutation problems

It is well known that the problem of maximization of any difference of convex functions can be turned into a convex maximization problem; here, the aim is a piecewise convex maximization problem instead. Although this may seem harder, sometimes the dimension may be reduced by 1, and the local search may be improved by using extreme points of the closure of the convex hull of better points. We show that it is always the case for both binary and permutation problems and give, as such instances, piecewise convex formulations for the maximum clique problem and the quadratic assignment problem.     

Parametric network utility maximization problem

We show how to solve the parametric utility maximization problem with a continuous parameter in a finite number of steps in order to obtain a solution with given accuracy. Also, we propose a new approach for the discretization of time for the parametric utility maximization problem with Lipschitz utility function. Some numerical results are provided.     

一类组合投资问题的线性规划解法

根据选定总体风险的一个上界值使组合投资的收益率达到最大的原则，并在合理简化的基础上建立组合投资决策问题的线性规划模型。然后通过算例求解带有参数的线性规划问题，给出资产组合的风险控制值和相应的最大净收益率及投资比例向量的关系。     

期货合约的简单创新

本文通过观察代办收入最大化交换,提出期货合约创新的一个简单两阶段模型. 经济代理商具有均值-方差偏好,按代理买卖量的大小,在期货合约过程中收取交易费用.期货交易过程中存在价差.代办收入最大化交换促成期货合约的创新.     

Undergraduate Students’ Quantitative Reasoning in Economic Contexts

Contributing to a growing body of research on undergraduate students’ quantitative reasoning, the study reported in this article used task-based interviews to investigate business calculus students’ quantitative reasoning when solving two optimization tasks situated in the context of revenue and profit maximization. Analysis of verbal responses and work written by 12 pairs of students during the task-based interviews revealed that nearly all pairs of students created new quantities (e.g., diminishing marginal returns). Students used these new quantities to reason about relationships among computer sales, sales discount, and total revenue in a revenue maximization task. The creation of these quantities helped the students to solve the problem posed in the task. Ten pairs of students interpreted marginal cost as total cost and marginal revenue as total revenue in a profit maximization task. Implications for business calculus instruction and directions for future research are discussed.     

Profit maximization with quantity discount: An application of geometric programming

Profit maximization is an important issue to the firms that pursue the largest economic profit possible. Traditionally, profit maximization problem is solved by differentiating with respect to input prices. The total differentiation of the first-order conditions might give complicated equations difficult to handle. Different from traditional studies, this paper considers input quantity discount and employs geometric programming technique to derive the objective value for the profit-maximization problem. The geometric programming approach not only gives the global optimum solution but also provides the information that is able to discover the relationship between profit maximization and returns to scale in the solution process. No differentiation is required. Moreover, geometric programming can provide a computationally attractive view of sensitivity analysis for the changes in parameters. Examples are given to illustrate the idea proposed in this paper.     

Maximum likelihood estimation of multinomial probit factor analysis models for multivariate t-distribution

We propose a model for multinomial probit factor analysis by assuming t-distribution error in probit factor analysis. To obtain maximum likelihood estimation, we use the Monte Carlo expectation maximization algorithm with its M-step greatly simplified under conditional maximization and its E-step made feasible by Monte Carlo simulation. Standard errors are calculated by using Louis’s method. The methodology is illustrated with numerical simulations.     

Performance guarantees of greedy algorithms for the problems on hereditary systems

Under study are the problems of maximization and minimization of additive functions on hereditary systems which generalize many computationally hard combinatorial optimization problems. A performance guarantee of the greedy algorithm is proven in terms of the parameters of a feasible set and the objective function of the maximization problem. This bound improves the well-known Jenkyns—Korte—Hausmann bound. An analogous result is obtained for the minimization problem of an additive function on a hereditary system.