Go home now Header Background Image
Search
Submission Procedure
share: |
 
Follow us
 
 
 
 
Volume 23 / Issue 7

available in:   PDF (393 kB) PS (935 kB)
 
get:  
Similar Docs BibTeX   Write a comment
  
get:  
Links into Future
 
DOI:   10.3217/jucs-023-07-0652

 

An Adaptive Membrane Evolutionary Algorithm for Solving Constrained Engineering Optimization Problems

Jianhua Xiao (Nankai University, China)

Ying Liu (Nankai University, China)

Shuai Zhang (University of Manitoba, Canada)

Ping Chen (Nankai University, China)

Abstract: In this paper, an adaptive membrane evolutionary algorithm (AMEA) is proposed, which combines a dynamic membrane structure and a differential evolution with the adaptive mutation factor. In the AMEA, the feasibility proportion method is used to dynamically adjust the size of the elementary membrane in the optimization process. The results of the experimental indicate that the proposed algorithm outperforms other evolutionary algorithms on five well-known constrained engineering optimization problems.

Keywords: differential evolution, engineering optimization problem, membrane algorithm, membrane computing

Categories: I.2.8