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Showing 2 results for Global Optimization

R. Sheikholeslami, A. Kaveh,
Volume 3, Issue 4 (10-2013)

This article presents a comprehensive review of chaos embedded meta-heuristic optimization algorithms and describes the evolution of this algorithms along with some improvements, their combination with various methods as well as their applications. The reported results indicate that chaos embedded algorithms may handle engineering design problems efficiently in terms of precision and convergence and, in most cases they outperform the results presented in the previous works. The main goal of this paper is to providing useful references to fundamental concepts accessible to the broad community of optimization practitioners.
F. Salajegheh , E. Salajegheh ,
Volume 11, Issue 2 (5-2021)

An ensemble method is introduced to solve optimization problems efficiently. The method is mainly based on using the gradient directions along which, the function is reduced at most. Large step sizes are employed for exploration in the first phase. The use of smaller step sizes in subsequence phases will allow for more accurate exploration. To increase the efficiency of the gradient techniques, some enhancements such as mutation, crossover and fly-back operations are introduced to explore the entire design space. The efficiency and the reliability of the multi-phase gradient approach are examined by solving 29 complicated multimodal functions introduced in CEC 2017 and a structural shape optimization problem under frequency constraints. The results are compared with several well-known population-based algorithms.

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