BSSA: Binary spring search algorithm

The applications of population-based heuristic optimization techniques, which randomly but guided search the optimization space, are increasing in variety of scientific realms. The idea behind most of these algorithms is based on physical phenomena or the behavior of creatures. In this paper, a novel heuristic optimization approach is introduced for finding the sub-optimal solutions of optimization problems. The proposed method is called the spring search algorithm (SSA), which is among the heuristic optimization techniques inspired from the physical rules where the search operators are a set of objects, and its binary version, which entitled binary spring search algorithm (BSSA), is formulated and investigated. The optimization results on a number of standard test functions show the efficacy of the proposed technique compared to those of the genetic algorithms and the improved version of the particle swarm optimization technique.