检索结果-内蒙古大学图书馆

OPTIMALITY CONDITIONS FOR ISOLATED LOCAL MINIMUM OF NONSMOOTH multiobjective problems

NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION 2015年第9期36卷 1087-1106页

作者： Ardali, A. Ansari Nobakhtian, S. Univ Isfahan Dept Math Esfahan Iran Inst Studies Theoret Phys & Math IPM Sch Math Tehran Iran

This article is devoted to the study of Fritz John and strong Kuhn-Tucker necessary conditions for properly efficient solutions, efficient solutions and isolated efficient solutions of a nonsmooth multiobjective optimization problem involving inequality and equality constraints and a set constraints in terms of the lower Hadamard directional derivative. Sufficient conditions for the existence of such solutions are also provided where the involved functions have pseudoconvex sublevel sets. Our results are based on the concept of pseudoconvex sublevel sets. The functions with pseudoconvex sublevel sets are a class of generalized convex functions that include quasiconvex functions.

关键词： Isolated minimum Lower Hadamard directional derivative multiobjective problems Optimality conditions Pseudoconvex sublevel sets 90C29 90C46

来源：评论

学校读者我要写书评

暂无评论

Solving multiobjective problems using cat swarm optimization

引用

EXPERT SYSTEMS WITH APPLICATIONS 2012年第3期39卷 2956-2964页

作者： Pradhan, Pyari Mohan Panda, Ganapati Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar Orissa India

This paper proposes a new multiobjective evolutionary algorithm (MOEA) by extending the existing cat swarm optimization (CSO). It finds the nondominated solutions along the search process using the concept of Pareto dominance and uses an external archive for storing them. The performance of our proposed approach is demonstrated using standard test functions. A quantitative assessment of the proposed approach and the sensitivity test of different parameters is carried out using several performance metrics. The simulation results reveal that the proposed approach can be a better candidate for solving multiobjective problems (MOPs). (C) 2011 Elsevier Ltd. All rights reserved.

关键词： multiobjective problems Evolutionary algorithm Swarm optimization Cat swarm optimization multiobjective cat swarm optimization Pareto dominance

来源：评论

学校读者我要写书评

暂无评论

Decomposition heuristics for multiobjective problems. The Food bank network redesign case

引用

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2024年 268卷

作者： Martins, C. L. Pato, M. V. Univ Lisbon ISEG Lisbon Sch Econ & Management REM CEMAPRE P-1200781 Lisbon Portugal Univ Lisbon Fac Ciencias CMAFcIO C6 P-1749016 Lisbon Portugal Univ Lisbon ISEG Lisbon Sch Econ & Management P-1200781 Lisbon Portugal

Large MO-MILP problems are often very hard to solve by exact methods. In this study we consider the Food bank network redesign (FBNR) problem to introduce three decompose-and-fix heuristics that successfully solve large real-life based instances of the problem. The FBNR problem is modeled as a multi-period, multi-product supply chain redesign problem that accounts for economic, environmental and social objectives in three distinct functions. Each new heuristic decomposes the FBNR problem into two MO-MILP problems, which are sequentially solved following the lexicographic concept. Decomposition observe the nature and terms of the decisions involved. The first MO-MILP problem concerns only the longer term decisions. After the corresponding decisions are fixed, the second MO-MILP problem referring to shorter term decisions is solved respecting the ranking of objectives followed for each solution obtained in the first problem. The difference among the heuristics lies in what is considered as longer or shorter term decisions. Besides solving large instances of the problem, which the exact method used could not do, CPU time savings generated by the heuristics range from 80% to 97% of the time required by the exact method. Compromise between the computational effort and the quality of solutions obtained by each heuristic is discussed. The solving methodology proposed in this study can be adapted to other large multiobjective problems.

关键词： Decompose-and-fix heuristics Lexicographic method multiobjective problems Sustainable supply chain

来源：评论

学校读者我要写书评

暂无评论

Fractional variational duality results for higher-order multiobjective problems

引用

JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS 2023年第2期40卷 1175-1201页

作者： Dhingra, Vivek Kailey, N. Thapar Inst Engn & Technol Sch Math Patiala India

This paper provides a study of multiobjective fractional variational programs involving support functions. It then explains the concept of higher-order K-eta convex. The paper's motivation is to study the duality results for the value of primal and dual programs. The numerical example of functional is discussed, which is higher-order K-eta convex but not first-order K-eta convex. A real-world example is considered to verify the results of the weak duality theorem.

关键词： Higher-order K-? convexity Ratio variational problems multiobjective problems Support functions

来源：评论

学校读者我要写书评

暂无评论

CONSTRAINT QUALIFICATIONS IN multiobjective OPTIMIZATION problems - DIFFERENTIABLE CASE

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1994年第3期80卷 483-500页

作者： MAEDA, T UNIV CALIF BERKELEY BERKELEY CA 94720 USA

In this paper, we are concerned with a multiobjective optimization problem with inequality constraints. We introduce a constraint qualification and derive the Kuhn-Tucker type necessary conditions for efficiency. More... 详细信息

关键词： CONSTRAINT QUALIFICATIONS EFFICIENCY PROPERLY EFFICIENT SOLUTIONS multiobjective problems LAGRANGE MULTIPLIERS

来源：评论

学校读者我要写书评

暂无评论

Infine functions and nonsmooth multiobjective optimization problems

引用

COMPUTERS & MATHEMATICS WITH APPLICATIONS 2006年第9-10期51卷 1385-1394页

作者： Nobakhtian, S. Univ Isfahan Dept Math Esfahan Iran

In this paper, we consider notion of infine functions and we establish necessary and sufficient optimality conditions for a feasible solution of a multiobjective optimization problem involving mixed constraints (equality and inequality) to be an efficient or properly efficient solution. We also obtain duality theorems for Wolf type and Mond-Weir type duals under the generalized invexity assumptions. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： multiobjective problems efficient solution duality infine functions nonsmooth analysis

来源：评论

学校读者我要写书评

暂无评论

A hybrid systematic design for multiobjective market problems: a case study in crude oil markets

引用

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2005年第4期18卷 495-509页

作者： Gholamian, MR Ghomi, SMTF Ghazanfari, M Amirkabir Univ Technol Dept Ind Engn Tehran 158754413 Iran Iran Univ Sci & Technol Dept Ind Engn Tehran 16844 Iran

This paper studies an application of hybrid systematic design in multiobjective market problems. The target problem is suggested as unstructured real world problem such that the objectives cannot be expressed mathematically and, only a set of historical data is utilized. Obviously, traditional methods and even meta-heuristic methods are broken in such cases. Instead, a systematic design using the hybrid of intelligent systems, particularly fuzzy rule base and neural networks can guide the decision maker towards noninferior solutions. The system does not stay in search phase. It also supports the decision maker in selection phase (after the search) to analyze various noninferior points and select the best ones based on the desired goal levels. In addition, numerical examples of real crude oil markets are provided to clarify the accuracy and performance of the developed system. (c) 2004 Elsevier Ltd. All rights reserved.

关键词： multiobjective problems fuzzy rule-based system neural networks crude oil markets

来源：评论

学校读者我要写书评

暂无评论

GPS： a constraint-based gene position procurement in chromosome for solving large-scale multiobjective multiple knapsack problems

引用

Frontiers of Computer Science 2018年第1期12卷 101-121页

作者： Jayanthi MANICASSAMY Dinesh KARUNANIDHI Sujatha POTHULA Vengattaraman THIRUMAL Dhavachelvan PONNURANGAM Subramanian RAMALINGAM Department of Computer Science Pondicherry University Pondicherry 605 014 India

The multiple knapsack problem （MKP） forms a base for resolving many real-life problems. This has also been considered with multiple objectives in genetic algorithms （GAs） for proving its efficiency. GAs use self- adaptability to effectively solve complex problems with constraints, but in certain cases, self-adaptability fails by converging toward an infeasible region. This pitfall can be resolved by using different existing repairing techniques; however, this cannot assure convergence toward attaining the optimal solution. To overcome this issue, gene position-based suppression （GPS） has been modeled and embedded as a new phase in a classical GA. This phase works on the genes of a newly generated individual after the recombination phase to retain the solution vector within its feasible region and to im- prove the solution vector to attain the optimal solution. Genes holding the highest expressibility are reserved into a subset, as the best genes identified from the current individuals by re- placing the weaker genes from the subset. This subset is used by the next generated individual to improve the solution vec- tor and to retain the best genes of the individuals. Each gene＇s positional point and its genotype exposure for each region in an environment are used to fit the best unique genes. Further, suppression of expression in conflicting gene＇s relies on the requirement toward the level of exposure in the environment or in eliminating the duplicate genes from the *** MKP benchmark instances from the OR-library are taken for the experiment to test the new model. The outcome por- trays that GPS in a classical GA is superior in most of the cases compared to the other existing repairing techniques.

关键词： combinatorial problems evolutionary algo-rithm multiobjective problems multiple knapsack problem,gene position effect gene suppression

来源：评论

学校读者我要写书评

暂无评论

Optimality criteria for nonsmooth continuous-time problems of multiobjective optimization

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2008年第1期136卷 69-76页

作者： Nobakhtian, S. Pouryayevali, M. R. Univ Isfahan Dept Math Esfahan Iran

A nonsmooth multiobjective continuous-time problem is introduced. We establish the necessary and sufficient optimality conditions under generalized convexity assumptions on the functions involved.

关键词： continuous-time programming multiobjective problems efficient solutions optimality conditions nonsmooth analysis

来源：评论

学校读者我要写书评

暂无评论

MOGBO: A new multiobjective Gradient-Based Optimizer for real-world structural optimization problems

引用

KNOWLEDGE-BASED SYSTEMS 2021年 218卷 106856-106856页

作者： Premkumar, Manoharan Jangir, Pradeep Sowmya, Ravichandran GMR Inst Technol Dept Elect & Elect Engn Rajam 532127 Andhra Pradesh India Rajasthan Rajya Vidyut Prasaran Nigam Ltd Sikar 332025 Rajasthan India Natl Inst Technol Dept Elect & Elect Engn Tiruchirappalli 620015 Tamil Nadu India

To handle the multiobjective optimization problems of truss-bar design, this paper introduces a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based on a recently reported single objective version of the gradient-based optimizer (GBO) inspired by the gradients of Newton's equations. The proposed algorithm is called as multiobjective gradient-based optimizer (MOGBO), in which two operators, such as local escaping operator and gradient search rule, and few vector sets are utilized in the search phase and the elitist non-dominated sorting mechanism is used for agent sorting to find Pareto optimal solutions. The proposed MOGBO is a posteriori method, and the traditional crowding distance mechanism is employed to confirm the coverage of the best solutions for the objectives of the given problem. The performance of the proposed MOGBO algorithm is verified and validated on different test cases, including 15 unconstraint benchmark test suites and eight constraint multiobjective truss bar design problems. To prove the superiority of the MOGBO algorithm, the performance is compared with state-of-the-art algorithms, such as multiobjective ant lion optimization (MOALO), multiobjective water cycle algorithm (MOWCA), multiobjective colliding bodies optimization (MOCBO), and non-dominated sorting gray wolf optimizer (NSGWO) in terms of metrics, such as hyper-volume, coverage, inverted generational distance, pure diversity, Spacing, Spread, coverage Pareto front, diversity maintenance, generational distance, and runtime. The solutions obtained by the proposed MOGBO algorithm is highly accurate and requires less runtime than the other selected algorithms. The obtained results also show the efficiency of the MOGBO in solving most of all the complex multiobjective problems. This research will be further backed up with external guidance for the future research at https://***/mysite. (c) 2021 Elsevier B.V. All rights reserve

关键词： Crowding distance Gradient-based optimizer (GBO) multiobjective Gradient-Based Optimizer (MOGBO) multiobjective problems Non-dominated sorting Structural design

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：