LoCost: A spatial social network algorithm for multi-objective optimisation

Particle swarm optimisation (PSO) is increasingly being applied to optimisation of problems in engineering design and scientific investigation. While readily adapted to single-objective problems, its use on multi-objective problems is hampered by the difficulty of finding effective means of guiding the swarm in the presence of multiple, competing objectives. This paper suggests a novel approach to this problem, based on an extension of the concepts of spatial social networks using a model of the behaviour of locusts and crickets. Comparison is made between neighbouring particles based on Pareto dominance, and a corresponding repulsion between particles added to previously suggested attractive forces. Computational experiments demonstrate that the new, spatial, social network optimisation algorithm can provide results comparable to a conventional MOPSO algorithm, and improved coverage of the Pareto-front.