Modified predator-prey algorithm for constrained and unconstrained multi-objective optimisation

Modifications of a well-known predator-prey evolutionary multi-objective optimisation algorithm based on the dynamics of predator-prey interactions existing in nature is presented. This algorithm is comprised of a relatively small number of predators and a much larger number of prey, randomly placed on a two dimensional lattice with connected ends. The predators are partially or completely biased towards one or more objectives, based on which each predator kills the weakest prey in its neighbourhood. A stronger prey created through evolution replaces this prey. In case of constrained problems, the sum of constraint violations serves as an additional objective. The prey remains stationary, while the predators move around in the lattice. Modifications have been implemented in this study regarding the selection procedure, apparent movement of the predators, mutation strategy, and dynamics of convergence to the Pareto front. Further alterations have been made making the algorithm capable of handling equality and inequality constraints. The final modified algorithm is tested on standard constrained and unconstrained multi-objective optimisation problems.