Population-based ant colony optimisation for multi-objective function optimisation

Ant inspired algorithms have recently gained popularity for use in multi-objective problem domains. The Population-based ACO, which uses a population of solutions as well as the traditional pheromone matrix, has been demonstrated as an effective problem solving strategy for solving combinatorial multi-objective optimisation problems, although this algorithm has yet to be applied to multi-objective function optimisation problems. This paper tests the suitability of a Population-based ACO algorithm for the multi-objective function optimisation problem. Results are given for a suite of problems of varying complexity.