Geodesy

Mechanism (biology)

Motion (physics)

Engineering optimization

Trigonometric functions

Algorithm

Benchmark (surveying)

Philosophy

Convergence (economics)

Operating system

Rounding

Economics

Particle swarm optimization

Computer science

Mathematical optimization

Interpolation (computer graphics)

Meta-optimization

Local optimum

Mathematics

Geography

Quadratic equation

Epistemology

Artificial intelligence

Geometry

Derivative-free optimization

Economic growth

Premature convergence

Optimization problem

Sine

Expert Systems with Applications

The sine cosine algorithm (SCA) is a well-known meta-heuristic optimization algorithm. SCA has received much attention in various optimization fields due to its simple structure and excellent optimization capabilities. However, the dimension of objective function also increases with the increasing complexity of optimization tasks. This makes the original SCA appear to have insufficient optimization capability and likely to fall into premature convergence. A multi-mechanism acting variant of SCA, called ARSCA, is proposed to address the above deficiencies. ARSCA is an enhanced SCA algorithm based on the adaptive quadratic interpolation mechanism (AQIM) and Rounding mechanism (RM). RM enables a more balanced state between exploration and exploitation of the ARSCA. AQIM enhances local exploitation capabilities. To verify the performance of ARSCA, we compared ARSCA with some advanced traditional optimization algorithms and variants of algorithms for 30 consecutive benchmark functions of IEEE CEC2014. In addition, ARSCA was applied to 6 constrained engineering optimization problems. These six algorithms include the tension–compression spring design problem, the welded beam design problem, the pressure vessel design problem, the I-beam design problem, the speed reducer design problem, and the three-bar design problem. Experimental results show that ARSCA outperforms its competitors in both the solution quality and the ability to jump out of the local optimum. The relevant codes for the paper are publicly available at https://github.com/YangXiao9799/paper_ARSCA.

An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems