The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Com base no princípio de seleção clonal proposto por Burnet, no processo de resposta imune não há cruzamento de material genético entre os membros do repertório, ou seja, não há comunicação de conhecimento durante diferentes pools de elite nos modelos de seleção clonal anteriores. Como resultado, o desempenho de pesquisa desses modelos é ineficaz. Para resolver este problema, inspirado no conceito da teoria da rede idiotípica, é apresentado um algoritmo de seleção clonal interativo lateral expandido (LICS). No LICS, um anticorpo amadurece não apenas através da hipermutação somática e da edição do receptor da célula B, mas também através dos estímulos de outros anticorpos. Os estímulos são realizados através da memorização de algum segmento genético comum nos idiótipos, com base no qual também é introduzido um operador de edição de receptor interativo lateral. Em seguida, o LICS é aplicado a diversas instâncias de referência do problema do caixeiro viajante. Os resultados da simulação mostram a eficiência e robustez do LICS quando comparado a outros algoritmos tradicionais.
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Shangce GAO, Hongwei DAI, Jianchen ZHANG, Zheng TANG, "An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 8, pp. 2223-2231, August 2008, doi: 10.1093/ietfec/e91-a.8.2223.
Abstract: Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.8.2223/_p
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@ARTICLE{e91-a_8_2223,
author={Shangce GAO, Hongwei DAI, Jianchen ZHANG, Zheng TANG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application},
year={2008},
volume={E91-A},
number={8},
pages={2223-2231},
abstract={Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.},
keywords={},
doi={10.1093/ietfec/e91-a.8.2223},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - An Expanded Lateral Interactive Clonal Selection Algorithm and Its Application
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2223
EP - 2231
AU - Shangce GAO
AU - Hongwei DAI
AU - Jianchen ZHANG
AU - Zheng TANG
PY - 2008
DO - 10.1093/ietfec/e91-a.8.2223
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2008
AB - Based on the clonal selection principle proposed by Burnet, in the immune response process there is no crossover of genetic material between members of the repertoire, i.e., there is no knowledge communication during different elite pools in the previous clonal selection models. As a result, the search performance of these models is ineffective. To solve this problem, inspired by the concept of the idiotypic network theory, an expanded lateral interactive clonal selection algorithm (LICS) is put forward. In LICS, an antibody is matured not only through the somatic hypermutation and the receptor editing from the B cell, but also through the stimuli from other antibodies. The stimuli is realized by memorizing some common gene segment on the idiotypes, based on which a lateral interactive receptor editing operator is also introduced. Then, LICS is applied to several benchmark instances of the traveling salesman problem. Simulation results show the efficiency and robustness of LICS when compared to other traditional algorithms.
ER -