Overview of Evolutionary Algorithms for Complex Constrained Optimization Problems

被引：0
|
作者：
Chen S.-M. [1 ]
Chen R. [1 ]
Liang W. [1 ]
Li R.-F. [2 ]
Li Z.-Y. [2 ]
机构：
[1] School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan
[2] College of Computer Science and Electronic Engineering, Hunan University, Changsha
来源：
Ruan Jian Xue Bao/Journal of Software | 2023年 / 34卷 / 02期
关键词：
constrained optimization; equality constraint; evolutionary algorithm; high computational expensive; high dimension; multi-objective;
D O I：
10.13328/j.cnki.jos.006711
中图分类号：
学科分类号：
摘要：
Most of engineering optimization problems can be formulated as constrained optimization problems. Evolutionary algorithms have been widely used in optimization constrained problems in recent years due to their sound performance. Nevertheless, the constraints make the solution space of the problem discrete, shrink and change, which bring great challenges to the evolutionary algorithm to solve the constrained optimization problem. The evolutionary algorithm integrating constraint handling technology has become a research hotspot. In addition, constraint processing techniques have been widely developed in the optimization of complex engineering application problems with the deepening of research in recent years, such as multi-objective, high-dimensional, equality constraint, etc. This study divides the evolutionary optimization for complex constraint optimization problems into evolutionary optimization algorithms for complex objectives and evolutionary algorithms for complex constraint scenarios according to the complexity. The challenges of constraint handling technology due to the complexity of practical engineering applications and the latest research progress in current research are discussed. Finally, the future research trends and challenges are summarized. © 2023 Chinese Academy of Sciences. All rights reserved.
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页码：565 / 581
页数：16
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