New Simple Trigonometric Algorithms for Solving Optimization Problems

Baskar A

《淡江理工學刊》 25卷6期 (2022/12) Pp. 1257-1272

https://doi.org/10.6180/jase.202212_25(6).0020

摘要

Heuristics play a key role in solving optimization problems with complex functions. They are popular as efficient heuristics are capable of providing results quickly with acceptable solution quality. Population-based heuristics are stochastic and hence, several iterations and trials are needed to achieve the expected accuracy and convergence to the global optimum. This article proposes two new, simple; population-based trigonometric algorithms, Sine (AB) and Cosine (AB). The algorithms are validated using forty well-known benchmark test functions available in the literature. The results are compared with a similar popular Sine Cosine Algorithm and the computational results show that the performance of Sine (AB) and Cosine (AB) are better than Sine Cosine Algorithm. Wilcoxon Signed-Rank and Friedman tests are carried out for statistical analyses. In addition to unconstrained functions, three real-world, constrained problems are solved to have a more intensive analysis of the proposed algorithms.

關鍵字

Optimization ； Population-based heuristic ； Un-constrained optimization ； Sine Cosine Algorithm ； Trigonometric Algorithm