Contents I. Introduction
Optimization has been always concerned and enumeration methods have been proposed to solve different kinds of optimization problems[1]. One of the most significant current discussions in optimization is how to obtain optimal solutions[2] for complex functions or functions with various constraints, wherein corresponding to actual problems in reality[3]–[5]. Therefore, many stochastic metaheuristics has been proposed with the principles of natural selection to guide a set of solutions toward the optimal one[6], [7]. Among them, Beetle Antennae Search Algorithm (BAS) is a novel bio-inspired heuristic optimization algorithm with the idea derived from the observation and study of the foraging process of beetles[8]. BAS has the advantages of few parameters, low computational complexity and easy implementation. BAS converges quickly in low-dimensional optimization functions and can be used to solve complex nonlinear optimization problems[9]. However, basic BAS has a lot to improve on[10], [11], to make it more effective and efficient in searching optimal solution to practice.
