检索结果-内蒙古大学图书馆

The gap function for optimization problems in Banach spaces

引用

NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS 2008年第2期69卷 716-723页

作者： Soleimani-damaneh, M. Teacher Training Univ Dept Mat Tehran 15618 Iran

关键词： multiple-objective optimization gap function variational inequality Clarke's gradient preinvexity

来源：评论

学校读者我要写书评

暂无评论

optimization models for training belief-rule-based systems

引用

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 2007年第4期37卷 569-585页

作者： Yang, Jian-Bo Liu, Jun Xu, Dong-Ling Wang, Jin Wang, Hongwei Univ Manchester Manchester Business Sch Manchester M15 6PB Lancs England Huazhong Univ Sci & Technol Inst Syst Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Peoples R China Hefei Univ Technol Hefei Peoples R China Univ Ulster Fac Engn Sch Comp & Math Jordanstown BT37 0QB Newtownabbey North Ireland Liverpool John Moores Univ Sch Engn Liverpool L3 3AF Merseyside England

A belief Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER) has been developed recently, where a new belief rule representation scheme is proposed to extend traditional IF-THEN rules. The belief rule expression matrix in RIMER provides a compact framework for representing expert knowledge. However, it is difficult to accurately determine the parameters of a belief rule base (BRB) entirely subjectively, particularly, for a large-scale BRB with hundreds or even thousands of rules. In addition, a change in rule weight or attribute weight may lead to changes in the performance of a BRB. As such, there is a need to develop a supporting mechanism that can be used to train, in a locally optimal way, a BRB that is initially built using expert knowledge. In this paper, several new optimization models for locally training a BRB are developed. The new models are either single- or multiple-objective nonlinear optimization problems. The main feature of these new models is that only partial input and output information is required, which can be either incomplete or vague, either numerical or judgmental, or mixed. The models can be used to fine tune a BRB whose internal structure is initially decided by experts' domain-specific knowledge or common sense judgments. As such, a wide range of knowledge representation schemes can be handled, thereby facilitating the construction of various types of BRB systems. Conclusions drawn from such a trained BRB with partially built-in expert knowledge can simulate real situations in a meaningful, consistent, and locally optimal way. A numerical study for a hierarchical rule base is examined to demonstrate how the new models can be implemented as well as their potential applications.

关键词： belief rule base (BRB) decision making evidential reasoning (ER) expert system inference multiple-objective optimization uncertainty

来源：评论

学校读者我要写书评

暂无评论

Optimal selection of encoding configuration for scalable video coding

Optimal selection of encoding configuration for scalable vid...

引用

IEEE International Conference on Image Processing (ICIP 2007)

作者： Abanoz, T. Berkin Tekalp, A. Murat Koc Univ Coll Engn TR-34450 Istanbul Turkey

ISBN: (纸本)9781424414369

It is well-known that the wider the range of extraction points a scalable bitstrearn supports, the lower the compression efficiency at these extraction points. Moreover, this compression efficiency generally varies according to what combination of scalability types are used to support this range of extraction points as specified by the encoding configuration. Hence, we propose some objective criteria as a measure of coverage, compression efficiency and rate-distortion performance of a configuration, and then present a multiple-objective optimization formulation to select the best encoding configuration for scalable video coding, given a range of bitstreams that must be supported. The method is demonstrated by experimental results.

关键词： scalable video coding encoding configuration multiple-objective optimization

来源：评论

学校读者我要写书评

暂无评论

optimization of constrained multiple-objective reliability problems using evolutionary algorithms

引用

RELIABILITY ENGINEERING & SYSTEM SAFETY 2006年第9期91卷 1057-1070页

作者： Salazar, Daniel Rocco, Claudio M. Galvan, Blas J. Univ Las Palmas Gran Canaria Div Computac Evolut & Aplicac CEANI Inst Sistemas Inteligentes & Aplicac Numer Ingn Islas Canarias Spain Cent Univ Venezuela Fac Ingn Caracas Venezuela

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation multiple-objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature. (C) 2005 Elsevier Ltd. All rights reserved.

关键词： constrained optimization MOEA multiple-objective optimization redundancy allocation and reliability optimization

来源：评论

学校读者我要写书评

暂无评论

Leader identification and leader selection: its effect on a swarm's performance for multi-objective design optimization problems

引用

STRUCTURAL AND MULTIDISCIPLINARY optimization 2004年第2-3期28卷 156-169页

作者： Liew, KM Tan, PK Ray, T Nanyang Technol Univ Nanyang Ctr Supercomp & Visualisat Singapore 639798 Singapore Nanyang Technol Univ Sch Mech & Prod Engn Singapore 639798 Singapore Natl Univ Singapore Singapore MIT Alliance High Performance Computat Engineered Syst Program Singapore 117548 Singapore Natl Univ Singapore Temasek Labs Singapore 117508 Singapore

In this paper, three distinct swarm strategies for the optimization of engineering design problems with multiple objectives are presented. These strategies build upon the swarm algorithm of Ray et al. by incorporating new processes which improve the performance of their predecessor. The constraint-matching strategy calls for the mating of solutions based on constraint satisfaction characteristics. Local search entails the thorough exploration of regions in parametric space where good solutions potentially reside. Migrating leaders prescribes the exchange of information between the best performing members of the swarm. As proof of their utility, the strategies were used to solve two well-studied optimal engineering design problems. Solutions obtained by the strategies are comparable with those of other optimization approaches documented in the literature.

关键词： engineering design multiple-objective optimization swarm strategy

来源：评论

学校读者我要写书评

暂无评论

A comparative study of multiple-objective metaheuristics on the bi-objective set covering problem and the Pareto memetic algorithm

引用

ANNALS OF OPERATIONS RESEARCH 2004年第1-4期131卷 135-158页

作者： Jaszkiewicz, A Poznan Univ Tech Inst Comp Sci PL-60965 Poznan Poland

The paper describes a comparative study of multiple-objective metaheuristics on the bi-objective set covering problem. Ten representative methods based on genetic algorithms, multiple start local search, hybrid genetic algorithms and simulated annealing are evaluated in the computational experiment. Nine of the methods are well known from the literature. The paper introduces also a new hybrid genetic algorithm called Pareto memetic algorithm. The results of the experiment indicate very good performance of hybrid genetic algorithms, however, no algorithm was able to outperform all other methods on all instances. Furthermore, the results indicate that the performance of multiple-objective metaheuristics may differ radically even if the methods are based on the same single objective algorithm and use exactly the same problem-specific operators.

关键词： multiple-objective optimization metaheuristics set covering problem

来源：评论

学校读者我要写书评

暂无评论

Optimality and Duality for Nondifferentiable multiple-objective optimization with Generalized Univexity

引用

Journal of Systems Science and Systems Engineering 2001年第2期13卷 162-172页

作者： ZHOU Hou-chun 1, QIU Yong-ping 21.Department of Mathematics, Shandong Linyi Teacher′s College, Shandong 276005, China2.Department of Mathematics, Shandong Jinan Educational College, Jinan 250002, China Department of Mathematics Shandong Linyi Teacher's College Shandong 276005 China Department of Mathematics Shandong Jinan Educational College Jinan 250002 China

Using generalized univex functions, a nondifferentiable multiple-objective optimization problem is ***-Tucker type sufficient optimality conditions are obtained for a feasible point to be an efficient or properly effi... 详细信息

关键词： multiple-objective optimization efficient solutions properly efficient solutions

来源：评论

学校读者我要写书评

暂无评论

multiple-objective risk-sensitive control and its small noise limit

引用

AUTOMATICA 2003年第3期39卷 533-541页

作者： Lim, AEB Zhou, XY Moore, JB Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA Australian Natl Univ Dept Syst Engn Canberra ACT 0200 Australia

This paper is concerned with a (minimizing) multiple-objective risk-sensitive control problem. Asymptotic analysis leads to the introduction of a new class of two-player, zero-sum, deterministic differential games. The distinguishing feature of this class of games is that the cost functional is multiple-objective in nature, being composed of the risk-neutral integral costs associated with the original risk-sensitive problem. More precisely, the opposing player in such a game seeks to maximize the most 'vulnerable' member of a given set of cost functionals while the original controller seeks to minimize the worst 'damage' that the opponent can do over this set. it is then shown that the problem of finding an efficient risk-sensitive controller is equivalent, asymptotically, to solving this differential game. Surprisingly, this differential game is proved to be independent of the weights on the different objectives in the original multiple-objective risk-sensitive problem. As a by-product, our results generalize the existing results for the single-objective risk-sensitive control problem to a substantially larger class of nonlinear systems, including those with control-dependent diffusion terms. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： risk-sensitive control multiple-objective optimization differential games Hamilton-Jacobi-Bellman equations upper/lower Isaacs equations viscosity solutions

来源：评论

学校读者我要写书评

暂无评论

Do multiple-objective metaheuristics deliver on their promises? A computational experiment on the set-covering problem

引用

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2003年第2期7卷 133-143页

作者： Jaszkiewicz, A Poznan Univ Tech Inst Comp Sci PL-60965 Poznan Poland

In this paper, we compare the computational efficiency of three state-of-the-art multiple-objective metaheuristics (MOMHs) and their single-objective counterparts on the multipleobjective set-covering problem (MOSCP). We use a methodology that allows consistent evaluation of the quality of approximately Pareto-optimal solutions generated by of both MOMHs and single-objective metaheuristics (SOMHs). Specifically, we use the average value of the scalarizing functions over a representative sample of weight vectors. Then, we compare computational efforts needed to generate solutions of approximately the same quality by the two kinds of methods. In the computational experiment, we use two SORMs-the evolutionary algorithm (EA) and the memetic algorithm (MA), and three MOMHs-controlled elitist nondominated sorting genetic algorithm, the strength Pareto EA, and the Pareto MA. The methods are compared on instances of the MOSCP with 2,3, and 4 objectives, 20,40,80 and 200 rows, and 200,400,800 and 1000 columns. The results of the experiment indicate good computational efficiency of the multiple-objective metaheuristics in comparison to their single-objective counterparts.

关键词： metaheuristics multiple-objective optimization set-covering problem

来源：评论

学校读者我要写书评

暂无评论

求解一种带有微分方程约束的条件变分问题的多目标最优化方法

引用

高等学校计算数学学报 2003年第4期25卷 289-295页

作者：李乃成西安交通大学理学院科学计算系西安 710049

按照电子光学理论,在静电透镜的设计中提出如下具有双目标泛函和微分方程约束的条件变分问题:

关键词： conditional variation multiple-objective optimization electrostatic lenses.

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：