An enhanced simulation-based design method coupled with meta-heuristic search algorithm for accurate reliability-based design optimization. (July 2016)

• Record Type: Journal Article
• Authors: Safaeian Hamzehkolaei, Naser; Miri, Mahmoud; Rashki, Mohsen
• Is Part Of: Engineering with computers. Volume 32:Number 3(2016)
• Page Start: 477
• Page End: 495
• Publication Date: 2016-07
• Subjects: Reliability-based design optimization -- Hybrid algorithm -- Weighted simulation method -- Particle swarm optimization -- Shift strategy; Engineering design -- Data processing -- Periodicals; Computer-aided design -- Periodicals; Conception technique -- Informatique -- Périodiques; Conception assistée par ordinateur -- Périodiques; Electronic journals; 620.00285
• DOI: 10.1007/s00366-015-0427-9
• Languages: English
• ISSNs: 0177-0667

Abstract

Abstract The enhanced weighted simulation-based design method in conjunction with particle swarm optimization (PSO) is developed as a pseudo double-loop algorithm for accurate reliability-based design optimization (RBDO). According to this hybrid method, generated samples of weighed simulation method (WSM) are considered as initial population of the PSO. The proposed population is then employed to evaluate the safety level of each PSO swarm (design candidates) during movement. Using this strategy, there is no required to conduct new sampling for reliability assessment of design candidates (PSO swarms). Employing PSO as the search engine of RBDO and WSM as the reliability analyzer provide more accurate results with few samples and also increase the application range of traditional WSM. Besides, a shift strategy is also introduced to increase the capability of the WSM to investigate general RBDO problems including both deterministic and random design variables. Several examples are investigated to demonstrate the accuracy and robustness of the method. Results demonstrate the computational efficiency and superiority of the proposed method for practical engineering problems with highly nonlinear and implicit probabilistic constrains.