Optimal design using clonal selection algorithm

Yi Hui Su, Wen Jye Shyr, Te Jen Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


In this paper, the Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. This paper synthesizes the advantages of clonal selection algorithm and proposed optimal design problem using clonal selection algorithm which is a basis of the immune system. CSA, the essence of immune algorithm, is effective to solve optimal problem. The clonal selection algorithm is highly parallel and presents a fine tractability in terms of computational cost. Like the genetic algorithm, clonal selection algorithm is a tool for optimum solution. Clonal selection algorithm and genetic algorithm are used to reach the optimization performances for two numerical function. Then those results are compared each other. These proposed algorithms are shown to be an evolutionary strategy capable of solving optimal design problem.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
PublisherSpringer Verlag
Number of pages7
ISBN (Print)3540288945, 9783540288947
Publication statusPublished - 2005 Jan 1
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 2005 Sep 142005 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3681 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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