Trigonometrics Functions Algorithm : a novel metaheuristic algorithm for engineering problems

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