The Parallel Predator-Prey Model: A Step towards Practical Application

In this paper, we apply the parallel predator-prey model for multi-objective optimization to a combinatorial problem for the first time: Exemplarily, we optimize sequences of 50 jobs for an instance of the bi-criteria scheduling problem 1|dj |Cj , Lmax with this approach. The modular building block architecture of the predator-prey system and the distribution of acting entities enables the analysis of separated problem knowledge and the design of corresponding variation operators. The actual modules are derived from local heuristics that tackle fractions of the complete problem. We unveil that it is possible to cover different areas of the Pareto-front with special property operators and make evident that the whole front can be covered if those operators are applied simultaneously to the spatial population. Further, we identify open problems that arise when the predator-prey model is applied to combinatorial problems which have not yet occurred for real-valued optimization problems.