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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Weijian Ren Qiong Wang Wei Lv Li Zhang | 
| Copyright Year | 2010 | 
| Description | Author affiliation: Faculty of Electric and Information Engineering, Daqing Petroleum Institute, Heilongjiang Province 163318, China (Weijian Ren; Qiong Wang; Wei Lv) || Oil Recovery Plant No.5, Daqing Oilfield Corp.Ltd, 163513, China (Li Zhang) | 
| Abstract | In order to overcome the shortcomings of Immune Genetic Algorithm's relatively slow convergence rate during the process of solving large-scale optimization problem, given Chaos optimization's benefits of sensitive to the initial value, easy to jump out of local minimum point, the fast search speed, global asymptotic convergence and so on, basing on the both search advantages of Immune Evolutionary Algorithm and Chaos Optimization Algorithm in their own space, considering that chaotic sequence could be simulated the proliferation of immune cells approach, we combined their characteristics of Chaos Optimization Algorithm and Immune Genetic Algorithm, making use of “exchange” and “shift” operations to solution matrix and memory matrix during the optimization process of chaos, and doing adaptive adjustment to selection probability and mutation probability during the Genetic operation, a kind of adaptive Immune Genetic Algorithm based on Chaos is proposed. The validity of the new algorithm is verified by real application. | 
| Starting Page | 5018 | 
| Ending Page | 5021 | 
| File Size | 471268 | 
| Page Count | 4 | 
| File Format | |
| ISBN | 9781424467129 | 
| e-ISBN | 9781424467129 | 
| DOI | 10.1109/WCICA.2010.5554661 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2010-07-07 | 
| Publisher Place | China | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Chaos Optimization Algorithm design and analysis Cities and towns Genetics Immune system Convergence TSP Immune Genetic Algorithm adaptive adjustment optimize | 
| Content Type | Text | 
| Resource Type | Article | 
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