Measuring mobility and the performance of global search algorithms

  • Authors:
  • Monte Lunacek;Darrell Whitley;James N. Knight

  • Affiliations:
  • Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

The global search properties of heuristic search algorithms are not well understood. In this paper, we introduce a new metric, mobility, that quantifies the dispersion of local optima visited during a search. This allows us to explore two questions: How disperse are the local optima visited during a search? How does mobility relate to algorithm performance? We compare local search with two evolutionary algorithms, CHC and CMA-ES, on a set of non-separable, non-symmetric, multi-modal test functions. Given our mobility metric, we show that algorithms visiting more disperse local optima tend to be better optimizers.