Research output per year
Research output per year
Personal profile
Personal profile
Benjamin Doerr is a full professor at École Polytechnique. His main research areas are algorithms (randomized algorithms) and artificial intelligence (heuristic search). He regularly teaches algorithms courses at École Polytechnique and in the MPRI Master program. He likes both a lot and thus does not spend much time on this homepage. You find some basic information below. His teaching can be found on the Polytechnique Moodle.
Research interests
Heuristic search, Evolutionary computation, Estimation of
distribution algorithms
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Collaborations and top research areas from the last five years
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A Crowding Distance That Provably Solves the Difficulties of the NSGA-II in Many-Objective Optimization
Zheng, W., Gao, Y. & Doerr, B., 1 Jan 2025, (Accepted/In press) In: IEEE Transactions on Evolutionary Computation.Research output: Contribution to journal › Article › peer-review
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Approximation Guarantees for the Nondominated Sorting Genetic Algorithm II (NSGA-II)
Zheng, W. & Doerr, B., 1 Jan 2025, In: IEEE Transactions on Evolutionary Computation. 29, 4, p. 891-905 15 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Difficulties of the NSGA-II With the Many-Objective LeadingOnes Problem
Doerr, B., Korkotashvili, D. & Krejca, M. S., 1 Jan 2025, (Accepted/In press) In: IEEE Transactions on Evolutionary Computation.Research output: Contribution to journal › Article › peer-review
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Evolutionary Algorithms Are Significantly More Robust to Noise When They Ignore It
Antipov, D. & Doerr, B., 1 Jan 2025, Proceedings of the 34th International Joint Conference on Artificial Intelligence, IJCAI 2025. Kwok, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 8842-8849 8 p. (IJCAI International Joint Conference on Artificial Intelligence).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
First Steps Toward a Runtime Analysis When Starting With a Good Solution
Antipov, D., Buzdalov, M. & Doerr, B., 15 May 2025, In: ACM Transactions on Evolutionary Learning and Optimization. 5, 2, 14.Research output: Contribution to journal › Article › peer-review
Open Access -
Hot off the Press: Speeding Up the NSGA-II With a Simple Tie-Breaking Rule
Doerr, B., Ivan, T. & Krejca, M. S., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 25-26 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Hot off the Press: Runtime Analysis of the Compact Genetic Algorithm on the LeadingOnes Benchmark
Chwiałkowski, M., Doerr, B. & Krejca, M. S., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 15-16 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Hot off the Press: Proven Runtime Guarantees for How the MOEA/D Computes the Pareto Front From the Subproblem Solutions
Doerr, B., Krejca, M. S. & Weeks, N., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 21-22 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Hot off the Press: Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms
Wietheger, S. & Doerr, B., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 85-86 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Hot off the Press: Runtime Analysis for Multi-Objective Evolutionary Algorithms in Unbounded Integer Spaces
Doerr, B., Krejca, M. S. & Rudolph, G., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 23-24 2 p. (GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access