Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions |
| |
| Authors: | Shiyuan Zhou Xue Peng Yinglin Wang Xiaoyun Xia |
| |
| Institution: | 1.School of Information Management and Engineering,Shanghai University of Finance and Economics,Shanghai,China;2.School of Mathematics and Systems Science,Guangdong Polytechnic Normal University,Guangzhou,China;3.Office of Budget and Finance,Jiaxing University,Jiaxing, Zhejiang,China;4.College of Mathematics, Physics and Information Engineering,Jiaxing University,Jiaxing, Zhejiang,China |
| |
| Abstract: | A simple immune-based multi-objective optimizer (IBMO) is proposed, and a rigorous running time analysis of IBMO on three proposed bi-objective pseudo-Boolean functions (Bi-Trap, Bi-Plateau and Bi-Jump) is presented. The running time of a global simple evolutionary multi-objective optimizer (GSEMO) using standard bit mutation operator with IBMO using somatic contiguous hypermutation (CHM) operator is compared with these three functions. The results show that the immune-based hypermutation can significantly beat standard bit mutation on some well-known multi-objective pseudo-Boolean functions. The proofs allow us to understand the relationship between the characteristics of the problems and the features of the algorithms more deeply. These analysis results also give us a good inspiration to analyze and design a bio-inspired search heuristics. |
| |
| Keywords: | |
| 本文献已被 CNKI SpringerLink 等数据库收录！ |
|
