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2020 – today
- 2022
[j44]Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
:
Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm. Algorithmica 84(6): 1603-1658 (2022)- [j43]Amirhossein Rajabi, Carsten Witt:
Self-Adjusting Evolutionary Algorithms for Multimodal Optimization. Algorithmica 84(6): 1694-1723 (2022) - [c71]Benjamin Doerr, Amirhossein Rajabi, Carsten Witt:
Simulated annealing is a polynomial-time approximation scheme for the minimum spanning tree problem. GECCO 2022: 1381-1389 - [c70]Frank Neumann, Dirk Sudholt, Carsten Witt:
The compact genetic algorithm struggles on Cliff functions. GECCO 2022: 1426-1433 - [c69]Frank Neumann, Carsten Witt:
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables. IJCAI 2022: 4800-4806 - [i32]Benjamin Doerr, Amirhossein Rajabi, Carsten Witt:
Simulated Annealing is a Polynomial-Time Approximation Scheme for the Minimum Spanning Tree Problem. CoRR abs/2204.02097 (2022) - [i31]Frank Neumann, Dirk Sudholt, Carsten Witt:
The Compact Genetic Algorithm Struggles on Cliff Functions. CoRR abs/2204.04904 (2022) - 2021
- [j42]Benjamin Doerr, Carsten Witt, Jing Yang:
Runtime Analysis for Self-adaptive Mutation Rates. Algorithmica 83(4): 1012-1053 (2021) - [j41]Johannes Lengler, Dirk Sudholt, Carsten Witt:
The Complex Parameter Landscape of the Compact Genetic Algorithm. Algorithmica 83(4): 1096-1137 (2021) - [j40]Andrew M. Sutton, Carsten Witt:
Lower Bounds on the Runtime of Crossover-Based Algorithms via Decoupling and Family Graphs. Algorithmica 83(10): 3180-3208 (2021) - [j39]Frank Neumann, Mojgan Pourhassan, Carsten Witt:
Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint. Algorithmica 83(10): 3209-3237 (2021) - [j38]Per Kristian Lehre, Carsten Witt:
Tail bounds on hitting times of randomized search heuristics using variable drift analysis. Comb. Probab. Comput. 30(4): 550-569 (2021) - [j37]Dogan Corus, Andrei Lissovoi, Pietro S. Oliveto, Carsten Witt:
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials Is Best. ACM Trans. Evol. Learn. Optim. 1(1): 2:1-2:38 (2021) - [c68]Amirhossein Rajabi, Carsten Witt:
Stagnation Detection with Randomized Local Search. EvoCOP 2021: 152-168 - [c67]Carsten Witt:
On crossing fitness valleys with majority-vote crossover and estimation-of-distribution algorithms. FOGA 2021: 2:1-2:15 - [c66]Amirhossein Rajabi, Carsten Witt:
Stagnation detection in highly multimodal fitness landscapes. GECCO 2021: 1178-1186 - [i30]Amirhossein Rajabi, Carsten Witt:
Stagnation Detection with Randomized Local Search. CoRR abs/2101.12054 (2021) - [i29]Dogan Corus, Andrei Lissovoi, Pietro S. Oliveto, Carsten Witt:
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials is Best. CoRR abs/2103.10394 (2021) - [i28]Amirhossein Rajabi, Carsten Witt:
Stagnation Detection in Highly Multimodal Fitness Landscapes. CoRR abs/2104.04395 (2021) - [i27]Frank Neumann, Carsten Witt:
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables. CoRR abs/2109.05799 (2021) - 2020
- [j36]Martin S. Krejca, Carsten Witt:
Lower bounds on the run time of the Univariate Marginal Distribution Algorithm on OneMax. Theor. Comput. Sci. 832: 143-165 (2020) - [c65]Carsten Witt:
Theory of estimation-of-distribution algorithms. GECCO Companion 2020: 1254-1282 - [c64]Amirhossein Rajabi, Carsten Witt:
Self-adjusting evolutionary algorithms for multimodal optimization. GECCO 2020: 1314-1322 - [c63]Pietro S. Oliveto, Dirk Sudholt, Carsten Witt:
A tight lower bound on the expected runtime of standard steady state genetic algorithms. GECCO 2020: 1323-1331 - [c62]Timo Kötzing, Carsten Witt:
Improved Fixed-Budget Results via Drift Analysis. PPSN (2) 2020: 648-660 - [c61]Amirhossein Rajabi, Carsten Witt:
Evolutionary Algorithms with Self-adjusting Asymmetric Mutation. PPSN (1) 2020: 664-677 - [p4]Martin S. Krejca, Carsten Witt:
Theory of Estimation-of-Distribution Algorithms. Theory of Evolutionary Computation 2020: 405-442 - [i26]Amirhossein Rajabi, Carsten Witt:
Self-Adjusting Evolutionary Algorithms for Multimodal Optimization. CoRR abs/2004.03266 (2020) - [i25]Timo Kötzing, Carsten Witt:
Improved Fixed-Budget Results via Drift Analysis. CoRR abs/2006.07019 (2020) - [i24]Amirhossein Rajabi, Carsten Witt:
Evolutionary Algorithms with Self-adjusting Asymmetric Mutation. CoRR abs/2006.09126 (2020) - [i23]Frank Neumann, Mojgan Pourhassan, Carsten Witt:
Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint. CoRR abs/2010.10885 (2020)
2010 – 2019
- 2019
- [j35]Benjamin Doerr, Christian Gießen, Carsten Witt, Jing Yang:
The ( $$1+\lambda $$ 1 + λ ) Evolutionary Algorithm with Self-Adjusting Mutation Rate. Algorithmica 81(2): 593-631 (2019) - [j34]Carsten Witt:
Upper Bounds on the Running Time of the Univariate Marginal Distribution Algorithm on OneMax. Algorithmica 81(2): 632-667 (2019) - [j33]Dirk Sudholt, Carsten Witt:
On the Choice of the Update Strength in Estimation-of-Distribution Algorithms and Ant Colony Optimization. Algorithmica 81(4): 1450-1489 (2019) - [c60]Hsien-Kuei Hwang, Carsten Witt:
Sharp bounds on the runtime of the (1+1) EA via drift analysis and analytic combinatorial tools. FOGA 2019: 1-12 - [c59]Carsten Witt:
Theory of estimation-of-distribution algorithms. GECCO (Companion) 2019: 1197-1225 - [c58]Frank Neumann, Mojgan Pourhassan, Carsten Witt:
Improved runtime results for simple randomised search heuristics on linear functions with a uniform constraint. GECCO 2019: 1506-1514 - [c57]Andrew M. Sutton, Carsten Witt:
Lower bounds on the runtime of crossover-based algorithms via decoupling and family graphs. GECCO 2019: 1515-1522 - [i22]Hsien-Kuei Hwang, Carsten Witt:
Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools. CoRR abs/1906.09047 (2019) - 2018
- [j32]Andrei Lissovoi, Carsten Witt:
The Impact of a Sparse Migration Topology on the Runtime of Island Models in Dynamic Optimization. Algorithmica 80(5): 1634-1657 (2018) - [j31]Christian Gießen, Carsten Witt:
Optimal Mutation Rates for the (1+ λ ) EA on OneMax Through Asymptotically Tight Drift Analysis. Algorithmica 80(5): 1710-1731 (2018) - [c56]Carsten Witt:
Theory of estimation-of-distribution algorithms. GECCO (Companion) 2018: 1170-1197 - [c55]Benjamin Doerr, Carsten Witt, Jing Yang:
Runtime analysis for self-adaptive mutation rates. GECCO 2018: 1475-1482 - [c54]Johannes Lengler, Dirk Sudholt, Carsten Witt:
Medium step sizes are harmful for the compact genetic algorithm. GECCO 2018: 1499-1506 - [c53]Carsten Witt:
Domino convergence: why one should hill-climb on linear functions. GECCO 2018: 1539-1546 - [i21]Martin S. Krejca, Carsten Witt:
Theory of Estimation-of-Distribution Algorithms. CoRR abs/1806.05392 (2018) - [i20]Benjamin Doerr, Carsten Witt, Jing Yang:
Runtime Analysis for Self-adaptive Mutation Rates. CoRR abs/1811.12824 (2018) - 2017
- [j30]Christian Gießen, Carsten Witt:
The Interplay of Population Size and Mutation Probability in the (1 + λ) EA on OneMax. Algorithmica 78(2): 587-609 (2017) - [j29]Andrei Lissovoi, Carsten Witt:
A Runtime Analysis of Parallel Evolutionary Algorithms in Dynamic Optimization. Algorithmica 78(2): 641-659 (2017) - [j28]Benjamin Doerr, Paul Fischer, Astrid Hilbert, Carsten Witt:
Detecting structural breaks in time series via genetic algorithms. Soft Comput. 21(16): 4707-4720 (2017) - [c52]Martin S. Krejca, Carsten Witt:
Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax. FOGA 2017: 65-79 - [c51]Benjamin Doerr, Christian Gießen, Carsten Witt, Jing Yang:
The (1+λ) evolutionary algorithm with self-adjusting mutation rate. GECCO 2017: 1351-1358 - [c50]Carsten Witt:
Upper bounds on the runtime of the univariate marginal distribution algorithm on onemax. GECCO 2017: 1415-1422 - [e3]Christian Igel, Dirk Sudholt, Carsten Witt:
Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2017, Copenhagen, Denmark, January 12-15, 2017. ACM 2017, ISBN 978-1-4503-4651-1 [contents] - [i19]Martin Ebbesen, Paul Fischer, Carsten Witt:
Edge-matching Problems with Rotations. CoRR abs/1703.09421 (2017) - [i18]Carsten Witt:
Upper Bounds on the Runtime of the Univariate Marginal Distribution Algorithm on OneMax. CoRR abs/1704.00026 (2017) - [i17]Benjamin Doerr, Christian Gießen, Carsten Witt, Jing Yang:
The (1+λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate. CoRR abs/1704.02191 (2017) - 2016
- [j27]Benjamin Doerr, Carsten Witt:
Guest Editorial: Theory of Evolutionary Computation. Algorithmica 75(3): 425-427 (2016) - [j26]Andrei Lissovoi, Carsten Witt:
MMAS Versus Population-Based EA on a Family of Dynamic Fitness Functions. Algorithmica 75(3): 554-576 (2016) - [c49]Dirk Sudholt, Carsten Witt:
Update Strength in EDAs and ACO: How to Avoid Genetic Drift. GECCO 2016: 61-68 - [c48]Christian Gießen, Carsten Witt:
Optimal Mutation Rates for the (1+λ) EA on OneMax. GECCO 2016: 1147-1154 - [c47]Andrei Lissovoi, Carsten Witt:
The Impact of Migration Topology on the Runtime of Island Models in Dynamic Optimization. GECCO 2016: 1155-1162 - [i16]Dirk Sudholt, Carsten Witt:
Update Strength in EDAs and ACO: How to Avoid Genetic Drift. CoRR abs/1607.04063 (2016) - 2015
- [j25]Andrei Lissovoi, Carsten Witt:
Runtime analysis of ant colony optimization on dynamic shortest path problems. Theor. Comput. Sci. 561: 73-85 (2015) - [j24]Pietro S. Oliveto, Carsten Witt:
Improved time complexity analysis of the Simple Genetic Algorithm. Theor. Comput. Sci. 605: 21-41 (2015) - [c46]Timo Kötzing, Andrei Lissovoi, Carsten Witt:
(1+1) EA on Generalized Dynamic OneMax. FOGA 2015: 40-51 - [c45]Christian Gießen, Carsten Witt:
Population Size vs. Mutation Strength for the (1+λ) EA on OneMax. GECCO 2015: 1439-1446 - [c44]Andrei Lissovoi, Carsten Witt:
On the Utility of Island Models in Dynamic Optimization. GECCO 2015: 1447-1454 - [c43]Frank Neumann, Carsten Witt:
On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling. IJCAI 2015: 3742-3748 - [i15]Frank Neumann, Carsten Witt:
On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling. CoRR abs/1504.06363 (2015) - 2014
- [j23]Carsten Witt:
Fitness levels with tail bounds for the analysis of randomized search heuristics. Inf. Process. Lett. 114(1-2): 38-41 (2014) - [j22]Pietro S. Oliveto, Carsten Witt:
On the runtime analysis of the Simple Genetic Algorithm. Theor. Comput. Sci. 545: 2-19 (2014) - [c42]Carsten Witt:
Revised analysis of the (1+1) ea for the minimum spanning tree problem. GECCO 2014: 509-516 - [c41]Carsten Witt:
Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. GECCO (Companion) 2014: 647-686 - [c40]Andrei Lissovoi, Carsten Witt:
MMAS vs. population-based EA on a family of dynamic fitness functions. GECCO 2014: 1399-1406 - [c39]Per Kristian Lehre, Carsten Witt:
Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift. ISAAC 2014: 686-697 - 2013
- [j21]Carsten Witt:
Tight Bounds on the Optimization Time of a Randomized Search Heuristic on Linear Functions. Comb. Probab. Comput. 22(2): 294-318 (2013) - [c38]Benjamin Doerr, Dirk Sudholt, Carsten Witt:
When do evolutionary algorithms optimize separable functions in parallel? FOGA 2013: 51-64 - [c37]Benjamin Doerr, Paul Fischer, Astrid Hilbert, Carsten Witt:
Evolutionary algorithms for the detection of structural breaks in time series: extended abstract. GECCO (Companion) 2013: 119-120 - [c36]Frank Neumann, Carsten Witt:
Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. GECCO (Companion) 2013: 567-590 - [c35]Benjamin Doerr, Thomas Jansen, Carsten Witt, Christine Zarges:
A method to derive fixed budget results from expected optimisation times. GECCO 2013: 1581-1588 - [c34]Andrei Lissovoi, Carsten Witt:
Runtime analysis of ant colony optimization on dynamic shortest path problems. GECCO 2013: 1605-1612 - [c33]Pietro S. Oliveto, Carsten Witt:
Improved runtime analysis of the simple genetic algorithm. GECCO 2013: 1621-1628 - [i14]Per Kristian Lehre, Carsten Witt:
General Drift Analysis with Tail Bounds. CoRR abs/1307.2559 (2013) - [i13]Carsten Witt:
The Fitness Level Method with Tail Bounds. CoRR abs/1307.4274 (2013) - 2012
- [j20]Anne Auger, Carsten Witt:
Theory of Randomized Search Heuristics. Algorithmica 64(4): 621-622 (2012) - [j19]Per Kristian Lehre, Carsten Witt:
Black-Box Search by Unbiased Variation. Algorithmica 64(4): 623-642 (2012) - [j18]Timo Kötzing, Frank Neumann, Heiko Röglin, Carsten Witt:
Theoretical analysis of two ACO approaches for the traveling salesman problem. Swarm Intell. 6(1): 1-21 (2012) - [j17]Carsten Witt:
Analysis of an iterated local search algorithm for vertex cover in sparse random graphs. Theor. Comput. Sci. 425: 117-125 (2012) - [c32]Frank Neumann, Carsten Witt:
Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. GECCO (Companion) 2012: 1035-1058 - [c31]Pietro S. Oliveto, Carsten Witt:
On the analysis of the simple genetic algorithm. GECCO 2012: 1341-1348 - [c30]Carsten Witt:
Optimizing Linear Functions with Randomized Search Heuristics - The Robustness of Mutation. STACS 2012: 420-431 - [i12]Pietro S. Oliveto, Carsten Witt:
Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation. CoRR abs/1211.7184 (2012) - 2011
- [j16]Pietro S. Oliveto, Carsten Witt:
Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation. Algorithmica 59(3): 369-386 (2011) - [j15]Benjamin Doerr, Frank Neumann, Dirk Sudholt, Carsten Witt:
Runtime analysis of the 1-ANT ant colony optimizer. Theor. Comput. Sci. 412(17): 1629-1644 (2011) - [c29]Martin Ebbesen, Paul Fischer, Carsten Witt:
Edge-Matching Problems with Rotations. FCT 2011: 114-125 - [c28]Carsten Witt:
Theory of randomized search heuristics in combinatorial optimization. GECCO (Companion) 2011: 1233-1260 - [c27]Benjamin Doerr, Mahmoud Fouz, Carsten Witt:
Sharp bounds by probability-generating functions and variable drift. GECCO 2011: 2083-2090 - [p3]Carsten Witt:
Theory of Particle Swarm Optimization. Theory of Randomized Search Heuristics 2011: 197-223 - [i11]Per Kristian Lehre, Carsten Witt:
Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation. CoRR abs/1105.5540 (2011) - [i10]Carsten Witt:
Tight Bounds on the Optimization Time of the (1+1) EA on Linear Functions. CoRR abs/1108.4386 (2011) - 2010
- [b2]Frank Neumann, Carsten Witt:
Bioinspired Computation in Combinatorial Optimization. Natural Computing Series, Springer 2010, ISBN 978-3-642-16543-6, pp. 1-203 - [j14]Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank Neumann, Carsten Witt:
Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective Models. Evol. Comput. 18(4): 617-633 (2010) - [j13]Dirk Sudholt, Carsten Witt:
Runtime analysis of a binary particle swarm optimizer. Theor. Comput. Sci. 411(21): 2084-2100 (2010) - [j12]Frank Neumann, Carsten Witt:
Ant Colony Optimization and the minimum spanning tree problem. Theor. Comput. Sci. 411(25): 2406-2413 (2010) - [c26]Timo Kötzing, Frank Neumann, Heiko Röglin, Carsten Witt:
Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem. ANTS Conference 2010: 324-335 - [c25]Frank Neumann, Dirk Sudholt, Carsten Witt:
A few ants are enough: ACO with iteration-best update. GECCO 2010: 63-70 - [c24]Per Kristian Lehre, Carsten Witt:
Black-box search by unbiased variation. GECCO 2010: 1441-1448 - [c23]Benjamin Doerr, Mahmoud Fouz, Carsten Witt:
Quasirandom evolutionary algorithms. GECCO 2010: 1457-1464 - [c22]Carsten Witt:
Theory of randomised search heuristics in combinatorial optimisation. GECCO (Companion) 2010: 2795-2840 - [e2]Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt:
Theory of Evolutionary Algorithms, 05.09. - 10.09.2010. Dagstuhl Seminar Proceedings 10361, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - [i9]Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt:
10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms 2010 - [i8]Per Kristian Lehre, Carsten Witt:
Black-Box Search by Unbiased Variation. Electron. Colloquium Comput. Complex. 17: 102 (2010)
2000 – 2009
- 2009
- [j11]Frank Neumann, Carsten Witt:
Runtime Analysis of a Simple Ant Colony Optimization Algorithm. Algorithmica 54(2): 243-255 (2009) - [j10]Thomas Jansen, Melanie Schmidt, Dirk Sudholt, Carsten Witt, Christine Zarges:
Ingo Wegener. Evol. Comput. 17(1): 1-2 (2009) - [j9]Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank Neumann, Carsten Witt:
Analyses of Simple Hybrid Algorithms for the Vertex Cover Problem. Evol. Comput. 17(1): 3-19 (2009) - [j8]Tobias Friedrich, Pietro S. Oliveto, Dirk Sudholt, Carsten Witt:
Analysis of Diversity-Preserving Mechanisms for Global Exploration. Evol. Comput. 17(4): 455-476 (2009) - [j7]Frank Neumann, Dirk Sudholt, Carsten Witt:
Analysis of different MMAS ACO algorithms on unimodal functions and plateaus. Swarm Intell. 3(1): 35-68 (2009) - [c21]Carsten Witt:
Why standard particle swarm optimisers elude a theoretical runtime analysis. FOGA 2009: 13-20 - [c20]Frank Neumann, Pietro S. Oliveto, Carsten Witt:
Theoretical analysis of fitness-proportional selection: landscapes and efficiency. GECCO 2009: 835-842 - [c19]Carsten Witt:
Theory of randomised search heuristics in combinatorial optimisation: an algorithmic point of view. GECCO (Companion) 2009: 3551-3592 - [c18]Carsten Witt:
Greedy Local Search and Vertex Cover in Sparse Random Graphs. TAMC 2009: 410-419 - [p2]Frank Neumann, Dirk Sudholt, Carsten Witt:
Computational Complexity of Ant Colony Optimization and Its Hybridization with Local Search. Innovations in Swarm Intelligence 2009: 91-120 - 2008
- [j6]Carsten Witt:
Population size versus runtime of a simple evolutionary algorithm. Theor. Comput. Sci. 403(1): 104-120 (2008) - [c17]Frank Neumann, Dirk Sudholt, Carsten Witt:
Rigorous Analyses for the Combination of Ant Colony Optimization and Local Search. ANTS Conference 2008: 132-143 - [c16]Dirk Sudholt, Carsten Witt:
Runtime analysis of binary PSO. GECCO 2008: 135-142 - [c15]Tobias Friedrich, Pietro S. Oliveto, Dirk Sudholt, Carsten Witt:
Theoretical analysis of diversity mechanisms for global exploration. GECCO 2008: 945-952 - [c14]