Multiobjective evolutionary algorithms for solving constrained optimization problems

被引：0

作者：

Sarker, Ruhul ^{[1
]}

Ray, Tapabrata ^{[2
]}

机构：

[1] Univ New South Wales, Australian Def Force Acad, Sch Informat Technol & Elect Engn, Canberra, ACT 2600, Australia

[2] Univ New South Wales, Australian Def Force Acad, Sch Aerosp Civil & Mech Engn, Canberra, ACT 2600, Australia

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION JOINTLY WITH INTERNATIONAL CONFERENCE ON INTELLIGENT AGENTS, WEB TECHNOLOGIES & INTERNET COMMERCE, VOL 2, PROCEEDINGS | 2006年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we compare two multi-objective evolutionary algorithms by solving bi-objective linear and nonlinear constrained optimization problems. The problems considered are three instances of a realistic crop planning problem. The multiobjective algorithms compared are a well-known multi-objective evolutionary algorithm NSGAII and our own algorithm MCA. We discuss the solutions obtained and analyse the sensitivity of variables for multiobjective solutions. From our analysis, it can be concluded that there is still room for improvement in the performance of the evolutionary optimization algorithms for some of these optimization problems.

引用

页码：197 / +

页数：2

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