Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
A Spatial Predator-Prey Approach to Multi-objective Optimization: A Preliminary Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Designing multi-objective variation operators using a predator-prey approach
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
An expertise-guided multi-criteria approach to scheduling problems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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The Predator Prey Model (PPM) for multi-objective evolutionary optimization features a simple abstraction from natural species interplay: predators represent different objectives and collectively hunt for prey solutions which have to adapt to all predators in order to survive. In this work, we start from previous insights to motivate significant changes in predators by enabling adaptation of selection behavior. For this, we integrate aspects of the ε-Constraint method into the PPM mechanisms. Our results show that this model extension results in good Pareto-fronts for bi-objective test problems.