检索结果-内蒙古大学图书馆

bilevel linear programming model of charging for effluent based on price control

Journal of Harbin Institute of Technology(New Series) 2007年第2期14卷 292-296页

作者：李煜华李磊胡运权邵海宏 College of Economics and Management Harbin University of Science and Technology Harbin 150040 China School of Management Harbin Institute of Technology Harbin 150001 China School of Management Harbin Institute of Technology

For the optimum price problem of charging for effluent, this paper analyzes the optimal Pigovian Tax and the serious information asymmetry problem existing in the application process of optimal Pigovian Tax, which is predominant in theory. Then the bilevel system optimizing decision-making theory is applied to give bilevel linear programming decision-making model of charging for effluent, in which the government (environmental protection agency) acts as the upper level decision-making unit and the polluting enterprises act as the lower level decision-making unit. To some extent, the model avoids the serious information asymmetry between the government and the polluting enterprises on charging for effluent.

关键词： charging for effluent Pigovian Tax price control bilevel linear programming information asymmetry

来源：评论

学校读者我要写书评

暂无评论

New branch-and-cut algorithm for bilevel linear programming

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2007年第2期134卷 353-370页

作者： Audet, C. Savard, G. Zghal, W. Ecole Hautes Etud Commerciales Gerad Montreal PQ Canada Ecole Polytech Montreal PQ H3C 3A7 Canada

linear mixed 0-1 integer programming problems may be reformulated as equivalent continuous bilevel linear programming (BLP) problems. We exploit these equivalences to transpose the concept of mixed 0-1 Gomory cuts to BLP. The first phase of our new algorithm generates Gomory-like cuts. The second phase consists of a branch-and-bound procedure to ensure finite termination with a global optimal solution. Different features of the algorithm, in particular, the cut selection and branching criteria are studied in details. We propose also a set of algorithmic tests and procedures to improve the method. Finally, we illustrate the performance through numerical experiments. Our algorithm outperforms pure branch-and-bound when tested on a series of randomly generated problems.

关键词： bilevel linear programming Gomory cuts linear mixed 0-1 integer programming branch-and-cut algorithms

来源：评论

学校读者我要写书评

暂无评论

Random fuzzy bilevel linear programming through possibility-based value at risk model

引用

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2014年第2期5卷 211-224页

作者： Katagiri, Hideki Uno, Takeshi Kato, Kosuke Tsuda, Hiroshi Tsubaki, Hiroe Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan Univ Tokushima Inst Socioarts & Sci Tokushima 7708502 Japan Hiroshima Inst Technol Fac Appl Informat Sci Saeki Ku Hiroshima 7315193 Japan Doshisha Univ Fac Sci & Engn Kyotanabe 6100394 Japan Inst Stat Math Tachikawa Tokyo 1908562 Japan

This article considers bilevel linear programming problems where random fuzzy variables are contained in objective functions and constraints. In order to construct a new optimization criterion under fuzziness and randomness, the concept of value at risk and possibility theory are incorporated. The purpose of the proposed decision making model is to optimize possibility-based values at risk. It is shown that the original bilevel programming problems involving random fuzzy variables are transformed into deterministic problems. The characteristic of the proposed model is that the corresponding Stackelberg problem is exactly solved by using nonlinear bilevel programming techniques under some convexity properties. A simple numerical example is provided to show the applicability of the proposed methodology to real-world hierarchical problems.

关键词： bilevel linear programming Random fuzzy variable Stackelberg solutions Possibility Value at risk

来源：评论

学校读者我要写书评

暂无评论

Optimistic Stackelberg solutions to bilevel linear programming with fuzzy random variable coefficients

引用

KNOWLEDGE-BASED SYSTEMS 2014年 67卷 206-217页

作者： Ren, Aihong Wang, Yuping Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China Baoji Univ Arts & Sci Dept Math Baoji 721013 Shaanxi Peoples R China

In this paper, we consider a kind of bilevel linear programming problem where the coefficients of both objective functions are fuzzy random variables. The purpose of this paper is to develop a computational method for obtaining optimistic Stackelberg solutions to such a problem. Based on alpha-level sets of fuzzy random variables, we first transform the fuzzy random bilevel programming problem into an alpha-stochastic interval bilevel linear programming problem. To minimize the interval objective functions, the order relations which represent the decision maker's preference are defined by the right limit and the center of random interval simultaneously. Using the order relations and expectation optimization, the alpha-stochastic interval bilevel linear programming problem can be converted into a deterministic multiobjective bilevel linear programming problem. According to optimistic anticipation from the upper level decision maker, the optimistic Stackelberg solution is introduced and a computational method is also presented. Finally, several numerical examples are provided to demonstrate the feasibility of the proposed approach. (C) 2014 Elsevier B.V. All rights reserved.

关键词： bilevel linear programming Fuzzy random variables Level sets Optimistic Stackelberg solutions Interval number Multiobjective

来源：评论

学校读者我要写书评

暂无评论

An interval programming approach for the bilevel linear programming problem under fuzzy random environments

引用

SOFT COMPUTING 2014年第5期18卷 995-1009页

作者： Ren, Aihong Wang, Yuping Xue, Xingsi Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China

In this paper, we address a class of bilevel linear programming problems with fuzzy random variable coefficients in objective functions. To deal with such problems, we apply an interval programming approach based on the -level set to construct a pair of bilevel mathematical programming models called the best and worst optimal models. Through expectation optimization model, the best and worst optimal problems are transformed into the deterministic problems. By means of the Kth best algorithm, we obtain the best and worst optimal solutions as well as the corresponding range of the objective function values. In this way, more information can be provided to the decision makers under fuzzy random circumstances. Finally, experiments on two examples are carried out, and the comparisons with two existing approaches are made. The results indicate the proposed approaches can get not only the best optimal solution (ideal solution) but also the worst optimal solution, and is more reasonable than the existing approaches which can only get a single solution (ideal solution).

关键词： bilevel linear programming Fuzzy random variables Interval programming Level sets Expectation optimization model

来源：评论

学校读者我要写书评

暂无评论

Random fuzzy bilevel linear programming through possibility-based fractile model

引用

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2014年第4期5卷 499-507页

作者： Sakawa, Masatoshi Matsui, Takeshi Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan

This paper focuses on random fuzzy noncooperative bilevel linear programming problems. Considering the probabilities that the decision makers' objective function values are smaller than or equal to target variables, fuzzy goals of the decision makers are introduced. Using the fractile model to optimize the target variables under the condition that the degrees of possibility with respect to the attained probabilities are greater than or equal to certain permissible levels, the original random fuzzy bilevel programming problems are reduced to deterministic ones. Extended concepts of Stackelberg solutions are introduced and computational methods are also presented. A numerical example is provided to illustrate the proposed method.

关键词： bilevel linear programming Random fuzzy variable Stackelberg solutions Possibility Fractile criteria optimization

来源：评论

学校读者我要写书评

暂无评论

An adaptive genetic algorithm for solving bilevel linear programming problem

引用

Applied Mathematics and Mechanics(English Edition) 2007年第12期28卷 1605-1612页

作者：王广民王先甲万仲平贾世会 School of Management China University of Geosciences Institute of Systems Engineering Wuhan University School of Mathematics and Statistics Wuhan University School of Science Wuhan University of Science and Technology

bilevel linear programming, which consists of the objective functions of the upper level and lower level, is a useful tool for modeling decentralized decision problems. Various methods are proposed for solving this problem. Of all the algorithms, the ge- netic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming. In this paper, we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation. In addition, some techniques are adopted not only to deal with the difficulty that most of the chromosomes maybe infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm. The performance of this proposed algorithm is illustrated by the examples from references.

关键词： bilevel linear programming genetic algorithm fitness value adaptive operator probabilities crossover and mutation

来源：评论

学校读者我要写书评

暂无评论

A note on a modified simplex approach for solving bilevel linear programming problems

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2000年第2期126卷 454-458页

作者： Campêlo, M Scheimberg, S Fed Univ Rio De Janeiro COPPE Sistemas Inst Matemat BR-21945970 Rio De Janeiro Brazil Univ Fed Ceara Dept Estat & Mat Aplicada BR-60455760 Fortaleza Ceara Brazil

We analyze the article "A modified simplex approach for solving bilevel linear programming problems" (EJOR, 67, 116-135). We point out some problems in its theoretical analysis. Moreover, the algorithm proposed may not find a global solution as it is claimed. We give some examples in order to illustrate these remarks. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： bilevel linear programming local and global optima penalty methods simplex method

来源：评论

学校读者我要写书评

暂无评论

An interval approach based on expectation optimization for fuzzy random bilevel linear programming problems

引用

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2015年第12期66卷 2075-2085页

作者： Ren, Aihong Wang, Yuping Baoji Univ Arts & Sci Baoji Shaanxi Peoples R China Xidian Univ Xian 710071 Shaanxi Peoples R China

This paper considers a class of bilevel linear programming problems in which the coefficients of both objective functions are fuzzy random variables. The main idea of this paper is to introduce the Pareto optimal solution in a multi-objective bilevel programming problem as a solution for a fuzzy random bilevel programming problem. To this end, a stochastic interval bilevel linear programming problem is first introduced in terms of alpha-cuts of fuzzy random variables. On the basis of an order relation of interval numbers and the expectation optimization model, the stochastic interval bilevel linear programming problem can be transformed into a multi-objective bilevel programming problem which is solved by means of weighted linear combination technique. In order to compare different optimal solutions depending on different cuts, two criterions are given to provide the preferable optimal solutions for the upper and lower level decision makers respectively. Finally, a production planning problem is given to demonstrate the feasibility of the proposed approach.

关键词： bilevel linear programming fuzzy random variables interval number programming Pareto optimal solution expectation optimization

来源：评论

学校读者我要写书评

暂无评论

Stackelberg solutions for fuzzy random bilevel linear programming through level sets and probability maximization

引用

OPERATIONAL RESEARCH 2012年第3期12卷 271-286页

作者： Sakawa, Masatoshi Katagiri, Hideki Matsui, Takeshi Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan

This paper considers Stackelberg solutions for bilevel linear programming problems under fuzzy random environments. To deal with the formulated fuzzy random bilevel linear programming problem, alpha-level sets of fuzzy random variables are introduced and an alpha-stochastic bilevel linear programming problem is defined for guaranteeing the degree of realization of the problem. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced and the alpha-stochastic bilevel linear programming problem is transformed into the problem to maximize the satisfaction degree for each fuzzy goal. Through probability maximization in stochastic programming, the transformed stochastic bilevel programming problem can be reduced to a deterministic bilevel programming problem. An extended concept of Stackelberg solution is introduced and a computational method is also presented. A numerical example is provided to illustrate the proposed method.

关键词： bilevel linear programming Fuzzy random variables Stackelberg solutions Level sets Probability maximization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：