Steady-state ALPS for real-valued problems

The objectives of this paper are to describe a steady-state version of the Age-Layered Population Structure (ALPS) Evolutionary Algorithm (EA) and to compare it against other GAs on real-valued problems. Motivation for this work comes from our previous success in demonstrating that a generational version of ALPS greatly improves search performance on a Genetic Programming problem. In making steady-state ALPS, some modifications were made to the method for calculating age and the method for moving individuals up age layers. To demonstrate that ALPS works well on real-valued problems we compare it against CMA-ES and Differential Evolution (DE) on five challenging, real-valued functions and on one real-world problem. While CMA-ES and DE outperform ALPS on the two unimodal test functions, ALPS is much better on the three multimodal test problems and on the real-world problem. Further examination shows that, unlike the other GAs, ALPS maintains a genotypically diverse population througho...

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Gregory S. Hornby
• Keywords: ALPS, Artificial Intelligence, De Outperform Alps, GECCO 2009, Steady-state Alps