Trigonometric Functions Algorithm : A Novel Metaheuristic Algorithm for Engineering Problems

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Résumé

This paper deals with the design of a novel metaheuristic algorithm called Trigonometric Functions Algorithm
(TFA) for efficient solving of engineering problems. The fundamental inspiration for this new algorithm is based on a
mathematical model inspired by the hunting and attack technique of grey wolves and using trigonometric functions. For
better exploration and exploitation of the search space, several random and adaptive variables are used. The various stages
of well-arranged TFA are described and mathematically modeled. In order to prove the effectiveness and robustness of
TFA, many engineering optimization problems of different difficulties were solved and a statistical study was made. The
optimization results obtained with TFA were compared with the results of other state-of-the-art algorithms. Statistical and
comparative studies showed that TFA achieves the best results and generally ranks first among the solved problems. The
study of the sensitivity of TFA related to several parameters shows that TFA has a high degree of stability giving it the ability
to efficiently solve optimization problems. In summary, the various studies have highlighted the efficiency, robustness and
superiority of TFA compared to other competing algorithms and thus allow us to conclude that TFA remains a better option
for solving technical design optimization problems.

Mots-clés

Optimization, engineering problems, metaheuristics, TFA.