XOR Binary Gravitational Search Algorithm

In this paper, an XOR binary gravitational search algorithm is introduced. Gravitational search algorithms, a physics inspired optimization algorithm, have previously been successfully applied to different real-valued optimization problems. In their binary version, the definition of a velocity vector changes to probability of change in corresponding dimensions. However, analysis shows that existing velocity vector update equation for binary gravitational search algorithm do not direct the particle towards better particle in certain cases. To apply this algorithm to binary optimization problems we introduce an XOR operator in the acceleration term. After a mathematical comparison to existing binary gravitational search algorithms it is shown that the proposed modification complies more with the definition of change in each dimension. Extensive simulations are performed showing the superiority of the proposed algorithm over other existing algorithms such as binary particle swarm optimization and an existing version of binary gravitational search algorithm.