Volume 10, Issue 1 (1-2020)                   2020, 10(1): 155-180 | Back to browse issues page

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Shahrouzi M, Salehi A. IMPERIALIST COMPETITIVE LEARNER-BASED OPTIMIZATION: A HYBRID METHOD TO SOLVE ENGINEERING PROBLEMS. International Journal of Optimization in Civil Engineering. 2020; 10 (1) :155-180
URL: http://ijoce.iust.ac.ir/article-1-427-en.html
Abstract:   (3332 Views)
Imperialist Competitive Algorithm, ICA is a meta-heuristic which simulates collapse of weak empires by more powerful ones that take possession of their colonies. In order to enhance performance, ICA is hybridized with proper features of Teaching-Learning-Based Optimization, TLBO. In addition, ICA walks are modified with an extra term to intensify looking for the global best solution. The number of control parameters and consequent tuning effort has been reduced in the proposed Imperialist Competitive Learner-Based Optimization, ICLBO with respect to ICA and several other methods. Efficiency and effectiveness of ICLBO is further evaluated treating a number of test functions in addition to continuous and discrete engineering problems. It is discussed and traced that balancing between exploration and exploitation is enhanced due to the proposed hybridization. Numerical results exhibit superior performance of ICLBO vs. ICA and a variety of other well-known meta-heuristics.
Full-Text [PDF 677 kb]   (179 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2019/12/31 | Accepted: 2019/12/31 | Published: 2019/12/31

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