Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Information Technology Journal
Year: 2006  |  Volume: 5  |  Issue: 3  |  Page No.: 524 - 528

Adaptive SAGA Based on Mutative Scale Chaos Optimization Strategy

Haichang Gao, Boqin Feng, Yun Hou, Bin Guo and Li Zhu    

Abstract: A hybrid adaptive SAGA based on mutative scale chaos optimization strategy (CASAGA) is proposed to solve the slow convergence, incident getting into local optimum characteristics of the Standard Genetic Algorithm (SGA). The algorithm combined the parallel searching structure of Genetic Algorithm (GA) with the probabilistic jumping property of Simulated Annealing (SA), also used adaptive crossover and mutation operators. The mutative scale Chaos optimization strategy was used to accelerate the optimum seeking. Compared with SGA and MSCGA on some complex function optimization and several TSP combination optimization problems, the CASAGA improved the global convergence ability and enhanced the capability of breaking away from local optimal solution.

Cited References   |    Fulltext    |   Related Articles   |   Back
 
 
   
 
 
 
  Related Articles

 
 
 
 
 
 
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility