Genetic algorithm for constrained global optimization in continuous variables
We present a stochastic global optimization algorithm, referred to as a Genetic Algorithm (GA), for solving constrained optimization problems over a compact search domain. It is a real-coded GA that converges in probability to the optimal solution. The constraints are treated through a repair operat...
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| Main Authors: | , |
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| 格式: | Article |
| 語言: | English |
| 出版: |
2014
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| 在線閱讀: | http://www.scopus.com/inward/record.url?eid=2-s2.0-28544431906&partnerID=40&md5=5ccb67a28e9ba11a4edbd9793b272221 http://cmuir.cmu.ac.th/handle/6653943832/4923 |
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| 總結: | We present a stochastic global optimization algorithm, referred to as a Genetic Algorithm (GA), for solving constrained optimization problems over a compact search domain. It is a real-coded GA that converges in probability to the optimal solution. The constraints are treated through a repair operator. A specific repair operator is included for linear inequality constraints. © 2005 Elsevier Inc. All rights reserved. |
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