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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
버넷(Burnet)이 제안한 클론 선택 이론에 기초한 클론 선택 알고리즘(CSA)은 지난 XNUMX년 동안 많은 관심과 폭넓은 적용을 받아왔습니다. 그러나 면역세포의 경우 증식과정은 무성이다. 즉, 서로 다른 면역 세포 간에는 정보 교환이 없습니다. 결과적으로 전통적인 CSA는 만족스럽지 못한 경우가 많으며 지역 최적점에 갇히기 쉬우므로 조기 수렴이 발생합니다. 이러한 문제를 해결하기 위해 양자 간섭 역학에서 영감을 받아 향상된 양자 교차 연산자가 도입되어 기존 CSA에 내장되었습니다. TSP(Traveling Salesman Problem)를 기반으로 한 시뮬레이션 결과는 양자 교차 기반 클론 선택 알고리즘의 효율성을 입증했습니다.
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부
Hongwei DAI, Yu YANG, Cunhua LI, Jun SHI, Shangce GAO, Zheng TANG, "Quantum Interference Crossover-Based Clonal Selection Algorithm and Its Application to Traveling Salesman Problem" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 1, pp. 78-85, January 2009, doi: 10.1587/transinf.E92.D.78.
Abstract: Clonal Selection Algorithm (CSA), based on the clonal selection theory proposed by Burnet, has gained much attention and wide applications during the last decade. However, the proliferation process in the case of immune cells is asexual. That is, there is no information exchange during different immune cells. As a result the traditional CSA is often not satisfactory and is easy to be trapped in local optima so as to be premature convergence. To solve such a problem, inspired by the quantum interference mechanics, an improved quantum crossover operator is introduced and embedded in the traditional CSA. Simulation results based on the traveling salesman problems (TSP) have demonstrated the effectiveness of the quantum crossover-based Clonal Selection Algorithm.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.78/_p
부
@ARTICLE{e92-d_1_78,
author={Hongwei DAI, Yu YANG, Cunhua LI, Jun SHI, Shangce GAO, Zheng TANG, },
journal={IEICE TRANSACTIONS on Information},
title={Quantum Interference Crossover-Based Clonal Selection Algorithm and Its Application to Traveling Salesman Problem},
year={2009},
volume={E92-D},
number={1},
pages={78-85},
abstract={Clonal Selection Algorithm (CSA), based on the clonal selection theory proposed by Burnet, has gained much attention and wide applications during the last decade. However, the proliferation process in the case of immune cells is asexual. That is, there is no information exchange during different immune cells. As a result the traditional CSA is often not satisfactory and is easy to be trapped in local optima so as to be premature convergence. To solve such a problem, inspired by the quantum interference mechanics, an improved quantum crossover operator is introduced and embedded in the traditional CSA. Simulation results based on the traveling salesman problems (TSP) have demonstrated the effectiveness of the quantum crossover-based Clonal Selection Algorithm.},
keywords={},
doi={10.1587/transinf.E92.D.78},
ISSN={1745-1361},
month={January},}
부
TY - JOUR
TI - Quantum Interference Crossover-Based Clonal Selection Algorithm and Its Application to Traveling Salesman Problem
T2 - IEICE TRANSACTIONS on Information
SP - 78
EP - 85
AU - Hongwei DAI
AU - Yu YANG
AU - Cunhua LI
AU - Jun SHI
AU - Shangce GAO
AU - Zheng TANG
PY - 2009
DO - 10.1587/transinf.E92.D.78
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2009
AB - Clonal Selection Algorithm (CSA), based on the clonal selection theory proposed by Burnet, has gained much attention and wide applications during the last decade. However, the proliferation process in the case of immune cells is asexual. That is, there is no information exchange during different immune cells. As a result the traditional CSA is often not satisfactory and is easy to be trapped in local optima so as to be premature convergence. To solve such a problem, inspired by the quantum interference mechanics, an improved quantum crossover operator is introduced and embedded in the traditional CSA. Simulation results based on the traveling salesman problems (TSP) have demonstrated the effectiveness of the quantum crossover-based Clonal Selection Algorithm.
ER -