A Genetic Algorithm with Constrained Sorting Method for Constrained Optimization Problems
Engineering problems are commonly optimization problems with various constraints. For solving these constrained optimization problems, an effective genetic algorithm with a constrained sorting method is proposed in this work. The constrained sorting method is based on a dynamic penalty function and a non-dominated sorting technique that is used for ranking all the feasible and infeasible solutions in the whole evolutionary population. The proposed algorithm is tested on five well-known benchmark functions and three engineering problems. Experimental results and comparisons with previously reported results demonstrate the effectiveness, efficiency and robustness of the present algorithm for constrained optimization problems.
genetic algorithm constrained optimization constraint handling dynamic penalty non-dominated sorting constrained sorting
Zhangjun Huang Chengen Wang Hong Tian
Key Laboratory of Process Industry Automation Northeastern University Shenyang,China School of Energy and Thermal Power Engineering Changsha University of Science and Technology Changsh
国际会议
上海
英文
806-811
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）