Abstract
Specular reflection algorithm (SRA) was a single population meta-heuristic algorithm inspired by the physical function of mirror. However, similar to most of meta-heuristic algorithms, it had the disadvantages of weak population diversity, stagnation in local optimal and low convergence rate. In order to overcome these shortcomings, a chaotic multi-specular reflection optimization algorithm considering shared nodes (CMSRAS) was proposed by the combination of population strategy with shared node, improved Tent chaos strategy and Gaussian mutation strategy. Initially, a single population SRA was extended to the multi-population with shared node and the population was initialized by improved Tent chaos sequence to improve the quality of the initial solution and the population diversity, and to enhance the global search ability. Meanwhile, to strengthen the local search ability and the convergence accuracy, the Gaussian mutation and improved Tent chaotic disturbance strategy were introduced into SRA. And then the influence law and sensitivity analysis of the CMSRAS algorithm between the initial setting parameters were obtained based on the response surface method and the Sobol's method. Finally, compared with both 12 state-of-the-art algorithms and 8 well-known advanced algorithms, the performance of CMSRAS was evaluated on a comprehensive set of 32 benchmark problems. In addition, CMSRAS was applied to solve the complex optimization problems of engineering structure. The results demonstrated that proposed CMSRAS algorithm outperformed most competitive algorithms and efficiently solve the real-life global optimization problems.
Highlights
Nowadays, with the continuous development of science and technology, engineering design is developing in the direction of lightweight, green intelligent manufacturing, high reliability etc
(3) Stability constraint In order to ensure the local stability of the flange plate of the main girder without the need for stiffening plate and reduce the manufacturing cost and avoid the stress concentration caused by too many welds during the processing of the main girder, a longitudinal stiffened plate should be added to the web
In this paper, in order to improve the performance of basic Specular reflection algorithm (SRA) algorithm, a chaotic multi-specular reflection optimization algorithm considering shared nodes (CMSRAS) is proposed on the combination of population strategy with shared nodes, improved Tent chaos strategy and Gaussian mutation strategy
Summary
With the continuous development of science and technology, engineering design is developing in the direction of lightweight, green intelligent manufacturing, high reliability etc. How to improve the performance of metaheuristic swarm intelligence optimization algorithms has been a hot issue problem by the way to the convergence accuracy, global search ability, the ability to resist local optimization etc. A multi-subpopulation based on symbiosis and non-uniform Gaussian mutation salp swarm algorithm (MSNSSA) was proposed to the overcome the disadvantages of slow convergence rate and low precision in salp swarm algorithm (SSA) [52] Another way is to improve the performance of meta-heuristic algorithm by using chaos theory and Gaussian mutation. In this paper, a novel chaotic multi-specular reflection optimization algorithm considering shared nodes (CMSRAS) was proposed by the combination of population strategy with shared node, improved Tent chaos strategy and Gaussian mutation strategy, respectively.
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