.png){kind=icon}
返回
Box-constrained multi-objective optimization: A gradient-like method without a priori scalarization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2007.05.015.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The aim of this paper is the development of an algorithm to find the critical points of a box-constrained multi-objective optimization problem. The proposed algorithm is an interior point method based on suitable directions that play the role of gradient-like directions for the vector objective function. The method does not rely on an a priori scalarization and is based on a dynamic system defined by a vector field of descent directions in the considered box. The key tool to define the mentioned vector field is the notion of vector pseudogradient. We prove that the limit points of the solutions of the system satisfy the Karush-Kuhn-Tucker (KKT) first order necessary condition for the box-constrained multi-objective optimization problem. These results allow us to develop an algorithm to solve box-constrained multi-objective optimization problems. Finally, we consider some test problems where we apply the proposed computational method. The numerical experience shows that the algorithm generates an approximation of the local optimal Pareto front representative of all parts of optimal front. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
multiple objective programming
gradient-like method
interior point method
descent directions
pseudogradient
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
引用论文
Mycochemical composition, bioactivities, and phylogenetic placement of three wild edible Russula species from Northern Odisha, India三个野生食用Russula种在印度北部奥里萨邦的真菌化学组成、生物活性及系统发育位置
PREAI
分享收藏Printable cellulose-based electroconductive composites for sensing elements in paper electronics
OAAI
OAAI分享收藏Optimizing culture conditions for establishment of hairy root culture of Semecarpus anacardium L..png)
3 BiotechOAAI
3 BiotechIF0
OAAI分享收藏
查看更多内容