Research project "Bridging the Gap between Theory and Practice in Nature-inspired Algorithms"
Funding agency and no.: Danish Council for Independent Research (DFF), 4002-00542
Abstract
Nature-inspired algorithms such as evolutionary algorithms and ant
colony optimization form a class of "off-the-shelf" heuristics for
optimization applied in practice when no problem-specific algorithm
is available. Despite huge empirical knowledge about nature-inspired
algorithms, there is only little theoretically guided advice on the
design and application of such algorithms. In particular, existing
theory gives little advice on the choice of the abundant parameters
that nature-inspired algorithms come with.
The aim of this research project is to bridge the gap between theory
in practice in nature-inspired algorithms by developing a practically
applicable
theory of complexity and parameter choice. Results are envisaged
which analyze the efficiency on classes of problems for realistic
problem sizes and determine the influence of common parameters such as search operators
and population size. Such results
are expected to improve the design of nature-inspired algorithms
and their applicability when optimization problems have to be
solved in our society.
Staff
News
- August 20, 2014: Recruitment process finished
- October 1, 2014: Project starts; PhD student Christian Gießen starts
- March 2015: Research article "Population Size vs. Mutation Strength for the (1+λ) EA on OneMax" by
Christian Gießen and Carsten Witt accepted as full paper
in the Theory Track at the Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, July 11-15, 2015
- July 2015: Christian attended GECCO 2015 conference in Madrid
- September 2015: Carsten and Christian attended 9th Workshop on Theory of Randomized Search Heuristics (ThRaSH 2015)
in Sheffield, UK
- March 2016: Carsten and Christian organized the
10th ThRaSH Workshop at DTU.
- April 2016: Research article "Optimal Mutation Rates for the (1+λ) EA on OneMax" by
Christian Gießen and Carsten Witt accepted as full paper
in the Theory Track at the Genetic and Evolutionary Computation Conference (GECCO 2016), Denver, July 20-24, 2016
- September 2016: Research article "The Interplay of Population Size and Mutation Probability in the (1+λ) EA on OneMax" by Christian Gießen and Carsten Witt published as journal article
in Algorithmica journal
- January 2017: Carsten co-organized FOGA 2017
- March 2017: Research article "The (1+λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate" by Benjamin Doerr,
Christian Gießen, Carsten Witt and Jing Yang accepted as full paper
in the Theory Track at the Genetic and Evolutionary Computation Conference (GECCO 2017), July 15-19, 2017
- March 2017: Research article "Upper Bounds on the Runtime of the Univariate Marginal
Distribution Algorithm on OneMax" by
Carsten Witt accepted as full paper
in the Theory Track at the Genetic and Evolutionary Computation Conference (GECCO 2017), July 15-19, 2017
- December 2017: Christian Gießen successfully defended his PhD thesis,
which includes several research results obtained in the project.