Lens Law Based Optimization Algorithm: A Novel Approach

Abstract

This paper explores the physics-based lens formula integrating through a population- based algorithm for solving any optimization problems. The object having multi-dimensional positions is the candidate of a solution of population creates image obstacles by a lens of convex, concave or combination of both. The position of the image is used to update the position of the object. The lens of concave, convex or combination of both emphasizes exploration, exploitation and local optima avoidance of the search space are the main objectives of the population-based optimization algorithms. The image formed by the object is governed by focal length equation which can be changed by defining the several random and adaptive variables to emphasize the exploitation and exploration of the search space. The ability of exploitation, exploration, use of search space, avoidance of local minima and reach to global maxima of the proposed algorithm is verified through unimodal, multimodal and composite benchmark functions. Besides the number of practical engineering problems are also considered for validation of performances of the proposed algorithm.