Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms

Publikation, 2017


A. Beham, E. Pitzer, S. Wagner, M. Affenzeller - Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms - Lecture Notes in Computer Science 10671, Las Palmas de Gran Canaria, Spanien, 2017, pp. 473-480


The no free lunch (NFL) theorem puts a limit to the range of problems a certain metaheuristic algorithm can be applied to success- fully. For many methods these limits are unknown a priori and have to be discovered by experimentation. With the use of tness landscape anal- ysis (FLA) it is possible to obtain characteristic data and understand why methods perform better than others. In past research this data has been gathered mostly by a separate set of exploration algorithms. In this work it is studied how FLA methods can be integrated into the meta- heuristic algorithm. We present a new exploratory method for obtaining landscape features that is based on path relinking (PR) and show that this characteristic information can be obtained faster than with tradi- tional sampling methods. Path relinking is used in several metaheuristic which creates the possibility of integrating these features and enhance algorithms to output landscape analysis in addition to good solutions.