Conference Proceedings

On the Selection of Fitness Landscape Analysis Metrics for Continuous Optimization Problems

Yuan Sun, Saman K Halgamuge, Michael Kirley, Mario A Munoz

2014 7TH INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION FOR SUSTAINABILITY (ICIAFS) | IEEE | Published : 2014

Abstract

Selecting the best algorithm for a given optimization problem is non-trivial due to large number of existing algorithms and high complexity of problems. A possible way to tackle this challenge is to attempt to understand the problem complexity. Fitness Landscape Analysis (FLA) metrics are widely used techniques to extract characteristics from problems. Based on the extracted characteristics, machine learning methods are employed to select the optimal algorithm for a given problem. Therefore, the accuracy of the algorithm selection framework heavily relies on the choice of FLA metrics. Although researchers have paid great attention to designing FLA metrics to quantify the problem characterist..

View full abstract