Special Relativity Search for applied mechanics and engineering

In this paper, Special Relativity Search (SRS) is developed for solving engineering problems. The interaction of particles in a magnetic field is considered as an optimizer model of the SRS in which the magnetic field is the feasible search space and the particles in this field are the possible design vectors. Particles interaction is investigated using the Lorentz force, velocity and distance between particles. Charged particles that move in opposite directions produce an inverse force and repel each other while charged particles that move in the same direction attract each other. The special relativity theory is implemented in an applicable way to develop SRS. In SRS, using the angular frequency, centripetal force, and inverse Lorentz transformations, main equations of the algorithm are developed. The design variables are randomly selected as a candidate for optimal answers from the initial population and updated their position in each iteration. This process continues until the global optimum is obtained. In this paper, to validate the SRS performance in solving engineering problems, total twenty-nine CEC-2017 Boundary Constraint (BC) problems and 12 engineering problems are optimized. To evaluate the superiority of the SRS algorithm, the results are compared with other well-known metaheuristic methods. Friedman's test is also used to rank the best algorithm. The results show a good performance of the SRS in most problems with the lowest computational cost.(c) 2022 Elsevier B.V. All rights reserved.