AbYSS: Adapting Scatter Search to Multiobjective Optimization

We propose the use of a new algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template for single objective optimization to the multiobjective domain. The result is a hybrid metaheuristic algorithm called AbYSS, which follows the scatter search structure but uses mutation and crossover operators from evolutionary algorithms. AbYSS incorporates typical concepts from the multiobjective field, such as Pareto dominance, density estimation, and an external archive to store the non-dominated solutions. We evaluate AbYSS with a standard benchmark including both unconstrained and constrained problems, and it is compared to two state-of-the-art multiobjective optimizers, NSGA-II and SPEA2. The results obtained indicate that, according to the benchmark and parameter settings used, AbYSS outperforms the other two algorithms as regards the diversity of the solutions, and it obtains very competitive results according to the convergence to the...

• Type: Journal
• Year: 2008
• Where: TEC
• Authors: Antonio J. Nebro, Francisco Luna, Enrique Alba, Bernabé Dorronsoro, Juan José Durillo, Andreas Beham
• Keywords: Algorithms, Multiobjective Optimization Problems, Scatter Search, TEC 2008