Return
Engineering design optimization using an improved local search based epsilon differential evolution algorithm
DOI:10.1007/s10845-016-1199-9.png)
Abstract
En 中文
Many engineering problems can be categorized into constrained optimization problems (COPs). The engineering design optimization problem is very important in engineering industries. Because of the complexities of mathematical models, it is difficult to find a perfect method to solve all the COPs very well. epsilon constrained differential evolution (epsilon DE) algorithm is an effectivemethod in dealing with the COPs. However, epsilon DE still cannot obtain more precise solutions. The interaction between feasible and infeasible individuals can be enhanced, and the feasible individuals can lead the population finding optimum around it. Hence, in this paper we propose a new algorithm based on e feasible individuals driven local search called as e constrained differential evolution algorithm with a novel local search operator (epsilon DELS). The effectiveness of the proposed epsilon DE-LS algorithm is tested. Furthermore, four real-world engineering design problems and a case study have been studied. Experimental results show that the proposed algorithm is a very effective method for the presented engineering design optimization problems.
Keywords:
Constrained optimization problems
Constraint handling technique
epsilon Constrained differential evolution
Local search operator
Engineering design optimization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.4
Papers:
3.5K
Citations:
1.1W

