中国碳生产率评估研究:方法与实证

碳生产率测评本质上是一个多目标规划问题,测评的具体标准联系于所设定模型的帕累托有效解.模型的不同,甚至求解方式的差异,都可确立不同的绩效测评标准.基于这一考虑,针对性构建了一个双目标规划问题,利用其像集确定问题的全部有效解,从而得到碳排放量与国内生产总值之间的有效对应关系,并设定其为碳生产率测评的一个参照标准.利用该标准,就1978-2014年间中国碳生产率状况进行了实证分析.结果表明,考察期内的中国碳生产率表现出先增后减的变化趋势,与传统碳生产率测评结果截然不同.     

多目标规划与福利评判标准

福利经济学的目标 ,是评价各种经济状态的“好”与“坏”.经济学家根据福利标准 ,进行政策评价 .因此 ,关于福利标准的研究是福利经济学中的重要问题之一 .帕累托最优是任一社会的最优经济状态都应满足的最起码和最没有争议的福利标准 ,但有时并不能反映真实的经济情况 .本文通过建立社会福利最优的多目标规划模型 ,用多目标规划理论 ,对社会福利最优状态和福利标准进行探讨 ,将帕累托最优标准推广到弱帕累托最优和非支配最优 .     

供应链中的多目标经济批量排产和运送问题的求解

当今供应链管理的目标已不再是只追求成本的最小化,越来越多的管理者和研究学者开始关注采用多个目标来对供应链的绩效进行优化.本文从一个供应商的角度出发,考虑了如何安排合理的生产排序来最小化生产周期和运送间隔以及最小化整条供应链中的单位时间的平均成本的批量排产和运送的问题.本文建立了该问题的多目标非线性混合整数规划模型,并提出了求解该问题的帕累托最优解集的方法.示例表明本文的算法是有效的.     

电热耦合综合能源系统双阶段多目标规划研究

多能耦合系统是未来分布式能源供给方式的重要发展方向。为了实现电热耦合能源供给系统的合理规划、促进能源供给与消费的经济与环保的协调发展,提出一种面向电热耦合能源系统的综合能源系统双阶段规划优化方法。模型的第一阶段是在投资和环境最优的目标下实现电热耦合综合能源系统的合理规划,第二阶段是在考虑设备运行特性的基础上对规划的结果进行运行优化,以获得能源系统的最优运行方案,并从多个指标验证规划方案的合理性。利用NSGA-II算法求得模型进的帕累托解集,使用多准则妥协优化法从帕累托解集中决策出最优配置方案。仿真结果表明,提出的双阶段多目标综合能源规划方法能够实现能源供给系统的经济与环保双优。     

基于混沌集群智能优化算法的多目标粗糙集属性约减

针对管理实践及大数据处理过程中具有多决策属性的粗糙集属性约减问题,将条件属性依赖度与知识分辨度进行结合构建属性权重,分别建立针对不同决策属性的约减目标函数,引入帕累托最优思想,将基于多决策属性的粗糙集属性约减问题转化为离散多目标优化问题。针对该问题的结构设计了具有集群智能优化思想的元胞自动机求解算法,在算法中引入基于个体的非支配解集平衡局部最优与全局最优的关系,引入混沌遗传算子增加种群多样性。以某铁路局设备安全风险处理数据为案例构建多决策属性粗糙集决策表进行优化计算并进行管理决策分析。研究发现:(1)相对于传统的NSGA-II与MO-cell算法,本文提出的算法具有更强的多目标属性挖掘性能;(2)帕累托最优思想可以较好地解释多决策属性粗糙集在管理实践中的意义。     

帕累托分布抽样基本定理及在帕累托分布参数估计中的应用

本文首先发现帕累托分布抽样基本定理,应用到帕累托分布参数估计中,得到了帕累托分布参数的一致最小方差无偏估计;并且得到了单总体帕累托分布参数的置信区间及联合置信区间,以及双总体帕累托分布参数比值的置信区间.     

多层规划和多目标规划的讨论

对任意给定的正整数 (n1,n2 ) ,构造了上下层决策变量分别是n1和n2 维的两层线性规划 ,其最优解不是相应双目标规划的有效解 ,进而构造出以任意给定的线性无关的向量d1,d2 为价格向量的两层规划 ,其最优解不是有效解 .这些讨论对现实问题的合理建模提供了理论依据 .此外 ,给出多层规划最优解是有效解的一个充分条件及判断其无效的方法 .     

一种新型劳务众包平台的市场策略与定价研究

定义并研究了自助式空间劳务众包这一新型众包模式,给出相关定义和众包平台的运行规则,提出会员行为仿真算法模拟市场.根据这类劳务众包平台增加利润和扩大市场份额的普遍需求,基于双边市场理论,提出任务打包机制、定价多目标规划模型和抢单顺序多目标规划模型.采用带精英策略的非支配排序的遗传算法(NSGA-Ⅱ)求解问题的帕累托解集(Pareto Front),最后应用逼近理想点法(TOPSIS)根据平台战略目标给出最优解.规划模型在数据集上应用效果良好,任务完成率能在有效控制成本的前提下提升30%至45%,新用户参与率能在保证较高的任务完成率的前提下提升150%至250%.     

动态需求背景下两阶段供应链博弈分析

在两阶段供应链中,市场营销也会导致需求的变动.引入营销费用与零售价格共同影响市场需求,并假设卖方决定订货批量,分别从非合作博弈和合作博弈两个角度对两阶段供应链管理问题进行分析.非合作博弈分析的是卖方或买方分别作为领导者时的Stackelberg模型;合作博弈是把卖方和买方的利润函数加权后作为目标函数,求出了帕累托最优解.结果证明,在合作博弈中存在帕累托有效解,与非合作博弈相比,合作博弈的订货批量更小,零售价格更低,市场营销费用更少.并列举案例,对模型中主要参数进行敏感性分析.     

有害废弃物处理站选址近似帕累托集合的有效产生

本文研究有害废弃物处理站选址问题。在Ravi等研究的MAX—MIN问题的基础上,考虑了处理站点容量的因素,建立了双目标优化问题,并给出了一个多项式时间算法,该算法能够产生一个（1,ε）一近似帕累托解集合。所得结论对实际的有害废弃物处理站选址决策具有理论意义,同时也完善了已有相关研究结果。     

Pareto Solutions of Polyhedral-valued Vector Optimization Problems in Banach Spaces

In general Banach spaces, we consider a vector optimization problem (SVOP) in which the objective is a set-valued mapping whose graph is the union of finitely many polyhedra. We establish some results on structure and connectedness of the weak Pareto solution set, Pareto solution set, weak Pareto optimal value set and Pareto optimal value set of (SVOP). In particular, we improve and generalize Arrow, Barankin and Blackwell’s classical results on linear vector optimization problems in Euclidean spaces.     

UNIFORM APPROXIMATION OF A MULTIOBJECTIVE OPTIMIZATION SEQUENCE

In this paper the Pareto efficiency of a uniformly convergent multiobjective optimization sequence is studied. We obtain some relation between the Pareto efficient solutions of a given multiobjective optimization problem and those of its uniformly convergent optimization sequence and also some relation between the weak Pareto efficient solutions of the same optimization problem and those of its uniformly convergent optimization sequence. Besides, under a compact convex assumption for constraints set and a certain convex assumption for both objective and constraint functions, we also get some sufficient and necessary conditions that the limit of solutions of a uniformly convergent multiobjective optimization sequence is the solution of a given multiobjective optimization problem.     

Constructing efficient solutions structure of multiobjective linear programming

It is not a difficult task to find a weak Pareto or Pareto solution in a multiobjective linear programming (MOLP) problem. The difficulty lies in finding all these solutions and representing their structure. This paper develops an algorithm for solving this problem. We investigate the solutions and their relationships in the objective space. The algorithm determines finite number of weights, each of which corresponds to a weighted sum problems. By solving these problems, we further obtain all weak Pareto and Pareto solutions of the MOLP and their structure in the constraint space. The algorithm avoids the degeneration problem, which is a major hurdle of previous works, and presents an easy and clear solution structure.     

Finding an efficient solution to linear bilevel programming problem: An effective approach

Multilevel programming is developed to solve the decentralized problem in which decision makers (DMs) are often arranged within a hierarchical administrative structure. The linear bilevel programming (BLP) problem, i.e., a special case of multilevel programming problems with a two level structure, is a set of nested linear optimization problems over polyhedral set of constraints. Two DMs are located at the different hierarchical levels, both controlling one set of decision variables independently, with different and perhaps conflicting objective functions. One of the interesting features of the linear BLP problem is that its solution may not be Paretooptimal. There may exist a feasible solution where one or both levels may increase their objective values without decreasing the objective value of any level. The result from such a system may be economically inadmissible. If the decision makers of the two levels are willing to find an efficient compromise solution, we propose a solution procedure which can generate effcient solutions, without finding the optimal solution in advance. When the near-optimal solution of the BLP problem is used as the reference point for finding the efficient solution, the result can be easily found during the decision process.     

Duality Theory in Fuzzy Optimization Problems

A solution concept of fuzzy optimization problems, which is essentially similar to the notion of Pareto optimal solution (nondominated solution) in multiobjective programming problems, is introduced by imposing a partial ordering on the set of all fuzzy numbers. We also introduce a concept of fuzzy scalar (inner) product based on the positive and negative parts of fuzzy numbers. Then the fuzzy-valued Lagrangian function and the fuzzy-valued Lagrangian dual function for the fuzzy optimization problem are proposed via the concept of fuzzy scalar product. Under these settings, the weak and strong duality theorems for fuzzy optimization problems can be elicited. We show that there is no duality gap between the primal and dual fuzzy optimization problems under suitable assumptions for fuzzy-valued functions.     

Totally balanced games arising from controlled programming problems

A cooperative game in characteristic-function form is obtained by allowing a number of individuals to esercise partial control over the constraints of a (generally nonlinear) mathematical programming problem, either directly or through committee voting. Conditions are imposed on the functions defining the programming problem and the control system which suffice to make the game totally balanced. This assures a nonempty core and hence a stable allocation of the full value of the programming problem among the controlling palyers. In the linear case the core is closely related to the solutions of the dual problem. Applications are made to a variety of economic models, including the transferable utility trading economies of Shapley and Shubik and a multishipper one-commodity transshipment model with convex cost functions and concave revenue functions. Dropping the assumption of transferable utility leads to a class of controlled multiobjective or ‘Pareto programming’ problems, which again yield totally balanced games.     

带阀点效应水火联合调度问题的一种半定凸松弛求解法

水火联合调度问题是电力系统中一类复杂的优化问题。合理安排调度周期内的水火电出力,确定一个最优发电计划,可以带来巨大的经济效益。在实际系统中,汽轮机调汽阀开启时出现的拔丝现象会使机组耗量特性产生阀点效应。忽略阀点效应,在一定程度上降低求解的精度。本文考虑带阀点效应的水火联合调度问题。该问题非凸非光滑,且带有非线性约束,直接使用确定性全局优化方法求解是相当困难的。本文使用高效的半定规划求解此问题。首先用耗量特性函数的初始周期代替其余有限的周期,并对其进行二次拉格朗日插值拟合。再通过引进0-1变量,得到整个耗量特性函数的近似,进而把问题松弛为半定规划模型。最后,采用凸规划应用软件包CVX求解一个仿真算例,得到一个近似全局最优解。     

高校教育成本测算及其优化管理模型

在高校成本层次分类的基础上,建立了生均成本测算的一般模型,针对教育成本投入过程中因学生人数随机变化而存在的风险,引进教学质量函数,提出了办学效益和教学质量的双目标优化模型.利用凸分析和优化原理得到优化问题解的存在性,全部正解的β取值范围以及最优解满足的充要条件,对最优解的定量计算给出了基于Monte Carlo模拟的遗传算法设计,并进行了相应的经济意义分析.     

A new fuzzy multi-objective programming: Entropy based geometric programming and its application of transportation problems

In this paper, we introduce a fuzzy mathematical programming with generalized fuzzy number as objective coefficients. We also examine a transportation problem with additional restriction. There is an additional entropy objective function in the transportation problem besides transportation cost objective function. Using new fuzzy mathematical programming, this multi-objective entropy transportation problem with generalized trapezoidal fuzzy number costs has been reduced to a primal geometric programming problem. Pareto optimal solution of the transportation model is found. Numerical examples have been provided to illustrate the problem.     

Sensitivity function: Properties and applications

The sensitivity function induced by a convex programming problem is examined. Its monotonicity, subdifferentiability, and closure properties are analyzed. A relation to the Pareto optimal solution set of the multicriteria convex optimization problem is established. The role of the sensitivity function in systems describing optimization problems is clarified. It is shown that the solution of these systems can often be reduced to the minimization of the sensitivity function on a convex set. Numerical methods for solving such problems are proposed, and their convergence is proved.