Andrew M Sutton

20062020
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Fingerprint The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.

Evolutionary algorithms Engineering & Materials Science
Evolutionary Algorithms Mathematics
Runtime Analysis Mathematics
Mutation Mathematics
Ant colony optimization Engineering & Materials Science
Fitness Mathematics
Complexity Analysis Mathematics
Polynomials Engineering & Materials Science

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Research Output 2006 2020

Parameterized complexity analysis of randomized search heuristics

Neumann, F. & Sutton, A. M., Jan 1 2020, Natural Computing Series. Springer, p. 213-248 36 p. (Natural Computing Series).

Research output: Chapter in Book/Report/Conference proceedingChapter

Parameterized Complexity
Complexity Analysis
Heuristic Search
Combinatorial optimization
Evolutionary algorithms

Lower bounds on the runtime of crossover-based algorithms via decoupling and family graphs

Sutton, A. M. & Witt, C., Jul 13 2019, GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, p. 1515-1522 8 p. (GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Decoupling
Crossover
Lower bound
Evolutionary algorithms
Graph in graph theory

On the empirical time complexity of scale-free 3-sat at the phase transition

Bläsius, T., Friedrich, T. & Sutton, A. M., Jan 1 2019, Tools and Algorithms for the Construction and Analysis of Systems - 25th International Conference, TACAS 2019, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019, Proceedings. Vojnar, T. & Zhang, L. (eds.). Springer Verlag, p. 117-134 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11427 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
Stochastic Search
Local Search
Time Complexity
Phase Transition
Backtracking

Runtime analysis of the (1+1) evolutionary algorithm for the chance-constrained knapsack problem

Neumann, F. & Sutton, A. M., Aug 27 2019, FOGA 2019 - Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. Association for Computing Machinery, Inc, p. 147-153 7 p. (FOGA 2019 - Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Runtime Analysis
Chance Constraints
Knapsack Problem
Evolutionary algorithms
Profit
1 Citation (Scopus)

When resampling to cope with noise, use median, not mean

Doerr, B. & Sutton, A. M., Jul 13 2019, GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, p. 242-248 7 p. (GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Resampling
Fitness
Polynomials
Logarithmic
Heuristic Optimization