Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions

doi:10.1007/s12204-018-2004-z

Journal of Shanghai Jiao Tong University (Science) ›› 2018, Vol. 23 ›› Issue (6): 827-833.doi: 10.1007/s12204-018-2004-z

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Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions

ZHOU Shiyuan (周诗源), PENG Xue (彭雪), WANG Yinglin (王英林), XIA Xiaoyun (夏小云)

(1. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China; 2. School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China; 3. Office of Budget and Finance, Jiaxing University, Jiaxing 314001, Zhejiang, China; 4. College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing 314001, Zhejiang, China)
(1. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China; 2. School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China; 3. Office of Budget and Finance, Jiaxing University, Jiaxing 314001, Zhejiang, China; 4. College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing 314001, Zhejiang, China)

Online:2018-12-01 Published:2018-12-07
Contact: PENG Xue (彭雪) E-mail: pxue2008@163.com

Abstract

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.

Key words: evolutionary algorithm | running time analysis | somatic contiguous hypermutation

摘要： 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.

关键词: evolutionary algorithm | running time analysis | somatic contiguous hypermutation

CLC Number:

TP 18

ZHOU Shiyuan (周诗源), PENG Xue (彭雪), WANG Yinglin (王英林), XIA Xiaoyun (夏小云). Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(6): 827-833.

References

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Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions

Rigorous Running Time Analysis of a Simple Immune-Based Multi-Objective Optimizer for Bi-Objective Pseudo-Boolean Functions

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