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Research Article 


Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan.

Abstract
Multi- objective optimization in structural applications is generally performed with the help of complex computer codes such as Finite Element Analysis (FEA) which are computationally very expensive. Surrogate models or meta- models are comparatively economical and very useful to optimize design solutions. In the earlier studies, authors have developed Advanced Surrogate Assisted Multi- objective Optimization Algorithm (ASAMO) by creating and selecting best single and mixture surrogate models for each offspring solution by Dempster- Shafer theory (DST). For this purpose MATSuMoTo, the MATLAB based tool box is modified for multi- objective optimization problems. In the present study, a Refined Advanced Surrogate Assisted Multi- objective Optimization Algorithm (RASAMO) is presented in which the quality of Pareto- Front of ASAMO algorithm is improved by adopting a Target Value Strategy. The effectiveness of Target Value Strategy is improved: (i) by adding multiple points per optimization iteration, and (ii) by developing most efficient surrogate models. RASAMO is applied to multi- objective machine tool spindle design problem. RASAMO resulted into 1.5% improvement in NHV value and 8.5% for the spread value for less number of function evaluations as compared to ASAMO. RASAMO is very easy to apply on benchmark and engineering applications.

Key words: Multi- Objective Optimization, MATSuMoTo, Surrogate Models, FEA, RASAMO


 
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How to Cite this Article
Pubmed Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. EEO. 2021; 20(5): 2374-2388. doi:10.17051/ilkonline.2021.05.259


Web Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. http://ilkogretim-online.org//?mno=61942 [Access: April 09, 2021]. doi:10.17051/ilkonline.2021.05.259


AMA (American Medical Association) Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. EEO. 2021; 20(5): 2374-2388. doi:10.17051/ilkonline.2021.05.259



Vancouver/ICMJE Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. EEO. (2021), [cited April 09, 2021]; 20(5): 2374-2388. doi:10.17051/ilkonline.2021.05.259



Harvard Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan (2021) Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. EEO, 20 (5), 2374-2388. doi:10.17051/ilkonline.2021.05.259



Turabian Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. 2021. Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. Elementary Education Online, 20 (5), 2374-2388. doi:10.17051/ilkonline.2021.05.259



Chicago Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. "Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO." Elementary Education Online 20 (2021), 2374-2388. doi:10.17051/ilkonline.2021.05.259



MLA (The Modern Language Association) Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan. "Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO." Elementary Education Online 20.5 (2021), 2374-2388. Print. doi:10.17051/ilkonline.2021.05.259



APA (American Psychological Association) Style

Shailesh S. Kadre, Vipin K. Tripathi, Hoi Huynh Tan (2021) Refined Advanced Surrogate Assisted Multi-Objective Optimization Algorithm- RASAMO. Elementary Education Online, 20 (5), 2374-2388. doi:10.17051/ilkonline.2021.05.259








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