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GECCO
2005
Springer

Measuring mobility and the performance of global search algorithms

12 years 3 days ago
Measuring mobility and the performance of global search algorithms
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. Categories and Subject Descriptors I.2.8 [Problem Solving, Control Methods, and Search]:
Monte Lunacek, L. Darrell Whitley, James N. Knight
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Monte Lunacek, L. Darrell Whitley, James N. Knight
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