Artificial immune optimization methods and applications - a survey

Inspired by natural immune systems, artificial immune systems (AIS) are an emerging kind of computational intelligence paradigm. During the past decade, the AIS have gained great research interest in wide engineering fields. Artificial immune optimization (AIO) methods are an important partner of the AIS. They have been successfully applied to deal with numerous challenging optimization problems with superior performance over classical optimization techniques. This paper gives a concise survey on the recent progresses of the theory as well as applications of the AIO schemes, in which some representative approaches are briefly introduced and discussed.

[1]  Zhou Ji,et al.  Artificial immune system (AIS) research in the last five years , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[2]  Hironori Hirata,et al.  An immunity based genetic algorithm and its application to the VLSI floorplan design problem , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[3]  Peter Ross,et al.  The evolution and analysis of potential antibody library for use in job-shop scheduling , 1999 .

[4]  Koji Yamada,et al.  Immune algorithm for n-TSP , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[5]  L.N. de Castro,et al.  An artificial immune network for multimodal function optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Hyun-Kyo Jung,et al.  Optimal design of synchronous motor with parameter correction using immune algorithm , 1997 .

[7]  Rajani R. Joshi Immune network memory: An inventory approach , 1995, Comput. Oper. Res..

[8]  Philippe Collard,et al.  Two models of immunization for time dependent optimization , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[9]  Song-Yop Hahn,et al.  A study on comparison of optimization performances between immune algorithm and other heuristic algorithms , 1998 .

[10]  E. Mizutani,et al.  Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review] , 1997, IEEE Transactions on Automatic Control.

[11]  Satoshi Endo,et al.  Evolutionary optimization algorithm using MHC and immune network , 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

[12]  Alan S. Perelson,et al.  Searching for Diverse, Cooperative Populations with Genetic Algorithms , 1993, Evolutionary Computation.

[13]  Alan S. Perelson,et al.  Using Genetic Algorithms to Explore Pattern Recognition in the Immune System , 1993, Evolutionary Computation.

[14]  Satoshi Endo,et al.  An immune optimization inspired by biological immune cell-cooperation for division-and-labor problem , 2001, Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001.

[15]  Shyh-Jier Huang,et al.  An immune-based optimization method to capacitor placement in a radial distribution system , 2000 .

[16]  C. A. Coello Coello,et al.  A parallel implementation of an artificial immune system to handle constraints in genetic algorithms: preliminary results , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[17]  Jerne Nk Towards a network theory of the immune system. , 1974 .

[18]  P. Hajela,et al.  Immune network simulations in multicriterion design , 1999 .

[19]  Jongsoo Lee,et al.  Constrained genetic search via schema adaptation: An immune network solution , 1996 .

[20]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[21]  Jiao Licheng,et al.  The immune evolutionary algorithm , 1999, 1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410).

[22]  Shyh-Jier Huang,et al.  Application of Immune-Based Optimization Method for Fault-Section Estimation in a Distribution System , 2002, IEEE Power Engineering Review.