Binary Optimisation with an Urban Pigeon-Inspired Swarm Algorithm

In this paper we introduce a metaheuristic for optimisation of discrete binary problems, derived from a recently proposed particle swarm algorithm inspired on the foraging behaviour of urban pigeons. The new variant of the algorithm is obtained by mapping the real-valued search space of the original version into a discrete binary-valued encoding. We illustrate the feasibility of the method on several binary benchmark problems and we study the impact of different running parameters such as problem dimension, population size and maximum number of evaluations. The potential of the method and possible extensions for improvement are also discussed.