New Hybrid Perturbed Projected Gradient and Simulated Annealing Algorithms for Global Optimization

被引:0
|
作者
Belkourchia, Yassin [1 ]
Es-Sadek, Mohamed Zeriab [1 ]
Azrar, Lahcen [1 ,2 ]
机构
[1] Mohammed V Univ Rabat, Res Ctr STIS, Dept Appl Math & Informat, ENSAM,M2CS, Rabat, Morocco
[2] King Abdulaziz Univ, Fac Engn, Dept Mech Engn, Jeddah, Saudi Arabia
关键词
Global optimization; Projected gradient; Stochastic perturbation; Simulated annealing; Constrained optimization; PARTICLE SWARM OPTIMIZATION; HARMONY SEARCH ALGORITHM; ANT COLONY OPTIMIZATION; ARTIFICIAL BEE COLONY; KRILL HERD ALGORITHM; ENGINEERING OPTIMIZATION; CONSTRAINED OPTIMIZATION; DIFFERENTIAL EVOLUTION; OPERATOR;
D O I
10.1007/s10957-023-02210-7
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The main objective of this works is to present an efficient hybrid optimization approach using a new coupling technique for solving constrained engineering design problems. This hybrid is based on the simulated annealing algorithm with the projected gradient and its stochastic perturbation. The proposed hybrid is combined with corrected techniques in order to correct the solutions out of domain and send them to the domain's border. The proposed algorithm is tested and evaluated on several benchmark functions, as well as on the basis of some engineering design problems. The obtained results are well compared with typical approaches existing in the literature. The solutions obtained by the proposed hybrid are more accurate than those given by other known methods and the performance and efficiency of the proposed algorithm are demonstrated.
引用
收藏
页码:438 / 475
页数:38
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