A General Framework for Multi-Objective Optimization Immune Algorithms

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Chen Yunfang 1,*

1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2012.06.01

Received: 4 Aug. 2011 / Revised: 3 Dec. 2011 / Accepted: 11 Feb. 2012 / Published: 8 Jun. 2012

Index Terms

Multi-Objective Optimization, Artificial Immune Systems, Algorithms Framework


Artificial Immune System (AIS) is a hotspot in the area of Computational Intelligence. While the Multi-Objective Optimization (MOP) problem is one of the most widely applied NP-Complete problems. During the past decade more than ten kinds of Multi-Objective optimization algorithms based on AIS were proposed and showed outstanding abilities in solving this kind of problem. The paper presents a general framework of Multi-Objective Immune Algorithms, which summarizes a uniform outline of this kind of algorithms and gives a description of its principles, mainly used operators and processing methods. Then we implement the proposed framework and build four typical immune algorithms on it: CLONALG, MISA, NNIA and CMOIA. The experiment results showed the framework is very suitable to develop the various multi-objective optimization immune algorithms.

Cite This Paper

Chen Yunfang, "A General Framework for Multi-Objective Optimization Immune Algorithms", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.6, pp.1-13, 2012. DOI:10.5815/ijisa.2012.06.01


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