检索结果-内蒙古大学图书馆

Random Descent Steps in a probability maximization Scheme

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2025年第1期205卷 1-26页

作者： Csizmas, Edit Drenyovszki, Rajmund Szantai, Tamas Fabian, Csaba I. John von Neumann Univ GAMF Fac Engn & Comp Sci Dept Informat Izsaki Ut 10 H-6000 Kecskemet Hungary Budapest Univ Technol & Econ Inst Math Dept Anal & Operat Res Muegyetem Rakpart 3 H-1111 Budapest Hungary

Gradient computation of multivariate distribution functions calls for considerable effort. Hence coordinate descent and derivative-free approaches are attractive. This paper deals with constrained convex problems. We perform random descent steps in an approximation scheme that is an inexact cutting-plane method from a dual viewpoint. We prove that the scheme converges and present a computational study comparing different descent methods applied in the approximation scheme.

关键词： Stochastic programming probability maximization Approximation schemes Coordinate-descent methods Cutting-plane methods

来源：评论

学校读者我要写书评

暂无评论

Stackelberg solutions for fuzzy random two-level linear programming through probability maximization with possibility

引用

FUZZY SETS AND SYSTEMS 2012年第1期188卷 45-57页

作者： Sakawa, Masatoshi Katagiri, Hideki Matsui, Takeshi Hiroshima Univ Grad Sch Engn Dept Cybernet Syst Higashihiroshima 7398527 Japan

This paper considers Stackelberg solutions for decision making problems in hierarchical organizations under fuzzy random environments. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced into the formulated fuzzy random two-level linear programming problems. On the basis of the possibility and necessity measures that each objective function fulfills the corresponding fuzzy goal, together with the introduction of probability maximization criterion in stochastic programming, we propose new two-level fuzzy random decision making models which maximize the probabilities that the degrees of possibility and necessity are greater than or equal to certain values. Through the proposed models, it is shown that the original two-level linear programming problems with fuzzy random variables can be transformed into deterministic two-level linear fractional programming problems. For the transformed problems, extended concepts of Stackelberg solutions are defined and computational methods are also presented. A numerical example is provided to illustrate the proposed methods. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Two-level linear programming Fuzzy random variable Stackelberg solutions Possibility Necessity probability maximization

来源：评论

学校读者我要写书评

暂无评论

Interactive fuzzy random cooperative two-level linear programming through level sets based probability maximization

引用

EXPERT SYSTEMS WITH APPLICATIONS 2013年第4期40卷 1400-1406页

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

In this paper, assuming cooperative behavior of the decision makers, two-level linear programming problems under fuzzy random environments are considered. To deal with the formulated fuzzy random two-level linear programming problems, alpha-level sets of fuzzy random variables are introduced and an alpha-stochastic two-level 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 two-level linear programming problem is transformed into the problem to maximize the satisfaction degree for each fuzzy goal. Through probability maximization, the transformed stochastic two-level programming problem can be reduced to a deterministic one. Interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Two-level linear programming problems Fuzzy random variables Level sets probability maximization Interactive decision making

来源：评论

学校读者我要写书评

暂无评论

Interactive fuzzy programming for fuzzy random two-level linear programming problems through probability maximization with possibility

引用

EXPERT SYSTEMS WITH APPLICATIONS 2013年第7期40卷 2487-2492页

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

This paper considers two-level linear programming problems involving fuzzy random variables under cooperative behavior of the decision makers. Through the introduction of fuzzy goals together with possibility measures, the formulated fuzzy random two-level linear programming problem is transformed into the problem to maximize the satisfaction degree for each fuzzy goal. By adopting probability maximization, the transformed stochastic two-level programming problem can be reduced to a deterministic one. Interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： Two-level programming Possibility probability maximization Interactive fuzzy decision making

来源：评论

学校读者我要写书评

暂无评论

Interactive fuzzy stochastic multi-level 0-1 programming using tabu search and probability maximization

引用

EXPERT SYSTEMS WITH APPLICATIONS 2014年第6期41卷 2957-2963页

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

In this paper, we consider interactive fuzzy programming for multi-level 0-1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0-1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0-1 programming problems. A numerical example for a three-level 0-1 programming problem is provided to illustrate the proposed method. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Multi-level programming Random variables Interactive fuzzy programming probability maximization Tabu search 0-1 Programming

来源：评论

学校读者我要写书评

暂无评论

Interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization

引用

OPERATIONAL RESEARCH 2014年第1期14卷 51-69页

作者： Yano, Hitoshi Sakawa, Masatoshi Nagoya City Univ Sch Humanities & Social Sci Mizuho Ku Nagoya Aichi 4678501 Japan Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan

This paper presents interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization. In our proposed approach, it is assumed that the decision maker has fuzzy goals for not only original objective functions but also the corresponding distribution functions in a probability maximization model, and such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy decision, such two kinds of membership functions are integrated. The satisfactory solution is derived from among an extended Pareto optimal solution set through the interaction with the decision maker. An illustrative numerical example is provided to demonstrate the efficiency of the proposed method.

关键词： Fuzzy random variable Fuzzy decision probability maximization Satisfactory solution Interactive decision making

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

Depth Map Upsampling via Progressive Manner Based on probability maximization 16th

Depth Map Upsampling via Progressive Manner Based on Probabi...

引用

16th Pacific-Rim Conference on Multimedia (PCM)

作者： Lin, Rongqun Zhang, Yongbing Wang, Haoqian Wang, Xingzheng Dai, Qionghai Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9783319240787;9783319240770

Depth maps generated by modern depth cameras, such as Kinect or Time of Flight cameras, usually have lower resolution and polluted by noises. To address this problem, a novel depth upsampling method via progressive manner is proposed in this paper. Based on the assumption that HR depth value can be generated from a distribution determined by the ones in its neighborhood, we formulate the depth upsampling as a probability maximization problem. Accordingly, we give a progressive solution, where the result in current iteration is fed into the next to further refine the upsampled depth map. Taking advantage of both local probability distribution assumption and generated result in previous iteration, the proposed method is able to improve the quality of upsampled depth while eliminating noises. We have conducted various experiments, which show an impressive improvement both in subjective and objective evaluations compared with state-of-art methods.

关键词： Progressive manner Denoising Depth map Upsampling probability maximization

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Approaches for Multiobjective Stochastic Linear Programming Problems Considering Both probability maximization and Fractile Optimization

Fuzzy Approaches for Multiobjective Stochastic Linear Progra...

引用

IEEE International Conference on Fuzzy Systems (FUZZ 2011)

作者： Yano, Hitoshi Nagoya City Univ Yamanohata Sch Humanities & Social Sci Mizuho Ku Nagoya Aichi 4678501 Japan

ISBN: (纸本)9781424473175

In this paper, we propose two kinds of fuzzy approaches to obtain a satisfactory solution for multiobjective stochastic linear programming problems, in which the criteria of probability maximization and fractile optimization are considered simultaneously. In the first approach, a probability maximization model is applied to multiobjective stochastic linear programming problems, where the decision maker is required to specify not permissible objective levels but the corresponding membership functions which represent fuzzy goals for permissible objective levels. By adopting the fuzzy decision to integrate both the membership functions for permissible objective levels and the ones for the probability functions, a probability maximization model is transformed to the maxmin problem without permissible objective levels as parameters. Similarly, in the second approach, a fractile optimization model is applied to multiobjective stochastic linear programming problems, where the decision maker is required to specify not permissible probability levels but the corresponding membership functions which represent fuzzy goals for permissible probability levels. By adopting the fuzzy decision to integrate both the membership functions for permissible probability levels and the ones for the objective functions, a fractile optimization model is transformed to the maxmin problem without permissible probability levels as parameters. It is shown that such two fuzzy approaches are same.

关键词： multiobjective stochastic linear programming probability maximization fractile optimization fuzzy decision

来源：评论

学校读者我要写书评

暂无评论

Interactive Fuzzy Programming through Possibility Measures and probability maximization for Two-Level Linear Programming Problems Involving Fuzzy Random Variable Coefficients

Interactive Fuzzy Programming through Possibility Measures a...

引用

IEEE International Conference on Fuzzy Systems (FUZZ 2011)

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

ISBN: (纸本)9781424473175

In this research, focusing on two-level linear programming problems involving fuzzy random variables, we propose a new decision making model through possibility measures. Taking into account vagueness of judgments of decision makers for each objective function, fuzzy goals are introduced. Noting that the degree of the possibility fluctuates stochastically, we propose a probability maximization model in stochastic programming. Through probability maximization, the transformed stochastic two-level programming problem can be reduced to a deterministic one. Interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented.

关键词： two-level programming possibility probability maximization interactive fuzzy decision making

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：