Evolutionary Optimization

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19 papers in the last four weeks, up 90% on the four weeks before. 0.2% of all new papers.

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Latest papers 196

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LLM-Driven Evolutionary Generation of Multi-Objective Bayesian Optimization Algorithms
Jul 6, 2026Georgios Laskaris, Reuben Brasher, Niki van Stein +3Automated Algorithm Discovery Evolutionary Optimization
Terra Quantum AG, Kornhausstrasse 25, 9000 St. Gallen, Switzerland · LIACS, Leiden University, Leiden, Netherlands
Dictionaries, Not Darwin: Set-Level Selection Beats LLM Evolution in Scientific Equation Discovery
Jul 5, 2026Pan LiEvolutionary Optimization Scientific Discovery
Independent Researcher
EvoOtter: Evolutionary Reproduction Test Generator
Jul 3, 2026Toufique Ahmed, Jatin Ganhotra, Avraham Shinnar +1Evolutionary Optimization LLM-Based Program Synthesis
IBM
Evolutionary Wave Function Collapse
Jul 2, 2026Dipika Rajesh, Ahmed Khalifa, Julian TogeliusEvolutionary Optimization Procedural Content Generation
UC Santa Cruz Santa Cruz, USA · University of Malta Msida, Malta · New York University New York, USA
Population-Based Multi-Objective Training of Discriminators for Semi-Supervised GANs
Jul 2, 2026Francisco Sedeño, Francisco Chicano, Jamal ToutouhEvolutionary Optimization Semi-Supervised Learning
ITIS Software, University of Malaga Malaga, Spain · CSAIL MIT, Cambridge, MA, USA
Novelty Search with Cross-Task Collaborative Discovery
Jul 1, 2026Jiao Liu, Yanchi Li, Hua Yu +2Novelty Search Evolutionary Optimization
College of Computing & Data Science, Nanyang Technological University, Singapore · School of Computer Science, China University of Geosciences · School of Intelligent Rail Transportation, Dalian Jiaotong University +1
Why can genetic algorithms work in high-dimensional search spaces?
Jun 29, 2026Stephen WhitelamEvolutionary Optimization Gradient Descent Dynamics
Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
Semantics-Aware Bilevel Co-Evolution: Towards Automated Multicomponent Algorithm Design
Jun 29, 2026Zhiyao Zhang, Shenghao Wu, Xingyu Wu +1Automated Algorithm Discovery Evolutionary Optimization
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China · College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
Jun 27, 2026Young-Jun Lee, Seungone Kim, Minki Kang +5Supervised Fine-Tuning Evolutionary Optimization
University of Minnesota · Carnegie Mellon University · KAIST +3
Analysis of Parameter Settings for the Bat Algorithm Using Variance Evolution
Jun 26, 2026Xin-She Yang, Mehmet KaramanogluExploration-Exploitation Tradeoff Evolutionary Optimization
Faculty of Science and Technology, Middlesex University, The Burroughs, London NW4 4BT, United Kingdom.
DE-2LS: Differential Evolution with Lightweight Late Local Search for Constrained Numerical Optimization
Jun 26, 2026Dikshit Chauhan, Anupam TrivediDifferential Evolution Evolutionary Optimization
Department of Electrical and Computer Engineering, National University of Singapore
DE-2LS: Differential Evolution with Late-Stage local-search for Unconstrained Single-Objective Numerical Optimization
Jun 26, 2026Dikshit ChauhanDifferential Evolution Evolutionary Optimization
Department of Electrical and Computer Engineering, National University of Singapore
Random Walk on Bézier Curves for Global Optimization
Jun 25, 2026Jinpeng Wang, Xingguo Xu, Yujing Sun +3Stochastic Optimization Evolutionary Optimization
aSchool of Computer Science, Northwestern Polytechnical University, Xi’an, 710129, China · bSchool of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China · cSchool of Mathematics, Hefei University of Technology, Hefei, 230601, China +3
The Red Queen Gödel Machine: Co-Evolving Agents and Their Evaluators
Jun 24, 2026Alex Iacob, Andrej Jovanović, William F. Shen +12Evolutionary Optimization AI Agent Evaluation
University of Cambridge · Flower Labs · NVIDIA +2
Bridging Spherical Black-Box Optimizers
Jun 24, 2026Johannes Ackermann, Stefano PeluchettiEvolutionary Optimization Black-Box Optimization
The University of Tokyo · Sakana AI
Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos
Jun 22, 2026Nima DehghaniEvolutionary Optimization Reservoir Computing
Department of Physics, MIT · McGovern Institute for Brain Research, MIT
SurGE: Surrogate Gradient-guided Evolution for Co-design of Legged Robots with Parallel Elasticity
Jun 20, 2026Yulun Zhuang, Yue Qin, Justin Lu +4Legged Robotics Surrogate-Assisted Optimization
Department of Robotics, University of Michigan, Ann Arbor, MI 48109, USA · Department of Mechanical and Aerospace Engineering, University of Tennessee, Knoxville, TN 37996, USA
On the Use of Survival Selection Methods for Evolutionary Diversity Optimisation
Jun 19, 2026Adel Nikfarjam, Jakob Bossek, Aneta Neumann +1Evolutionary Optimization Quality-Diversity Optimization
Optimisation and Logistics School of Computer Science Adelaide University · Department of Computer Science Machine Learning and Optimisation Paderborn University
Provably Sub-Linear Two-Timescale NeuroEvolution with Online Plasticity
Jun 18, 2026Shishen Lin, Yixin ChenRL Control Evolutionary Optimization
Department of Statistics, University of Warwick, Coventry, United Kingdom · 2Biozentrum, University of Basel, Basel, Switzerland
Evolutionary Two-Stage Hyperparameter Optimization Strategies for Physics-Informed Neural Networks
Jun 18, 2026Fedor Buzaev, Dmitry Efremenko, Egor Bugaev +4Multi-Fidelity Optimization Evolutionary Optimization
HSE University · 1HSE University · AXXX +1
Residual-Space Evolutionary Optimization via Flow-based Generative Models
Jun 18, 2026Zhuo Cao, Lena Krieger, Fernanda Nader +3Evolutionary Optimization Causal Counterfactual Generation
IAS-8, Forschungszentrum Jülich, Germany · LMU Munich, Munich Center for Machine Learning (MCML), Germany · Department of Computer Science, Aarhus University, Denmark.
Weight Adaptation for Improving Parallel Performance of Adaptive Stochastic Natural Gradient
Jun 18, 2026Yutaro Yamada, Kento Uchida, Shinichi ShirakawaEvolutionary Optimization Black-Box Optimization
Yokohama National University, Kanagawa, Japan
Model Merging to Evolution: Parameter Space Exploration for Expert Models
Jun 17, 2026Chao Wang, Yuchen Guo, Zheng Tan +4Evolutionary Optimization Evolution Strategies
School of Artificial Intelligence, Xidian University, Xi’an, China · School of Computer Science, University of Birmingham, Birmingham, UK · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China +3
Constraint-aware Optimization in Auto-Tuning
Jun 17, 2026Floris-Jan Willemsen, Stijn Heldens, Rob V. van Nieuwpoort +1Differential Evolution Evolutionary Optimization
LIACS, Leiden University, the Netherlands · Netherlands eScience Center, Amsterdam, the Netherlands
REFLEX: Reflective Evolution from LLM Experience
Jun 15, 2026Pan WangEvolutionary Optimization Large Language Model-Guided Optimization
University of Science and Technology of China, China.
MSC-CMA-ES: Structure-Aware Restarts for CMA-ES via Cyclic Nearest-Better Basin Discovery
Jun 14, 2026Dimitar Nedanovski, Svetoslav Nenov, Dimitar PilevEvolutionary Optimization Covariance Matrix Adaptation Evolution Strategy
Faculty of Mathematics and Informatics Sofia University St. Kliment Ohridski James Baucher Blvd., 1164 Sofia, Bulgaria · Department of Mathematics University of Chemical Technology and Metallurgy Sofia, Bulgaria · Department of Informatics University of Chemical Technology and Metallurgy Sofia, Bulgaria
Large Language Model-Driven Cooperative Operator Ensemble Evolution for Permutation Flow Shop Scheduling
Jun 13, 2026Rui Xu, Yufan Liao, Haoze Lv +3Evolutionary Optimization Metaheuristic Optimization
School of Business, Hohai University, Nanjing 211100, China · Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · School of Engineering and Computer Science, Victoria University of Wellington, Wellington 6140, New Zealand
Comparison Patrols on Drifting Orders: Certified Rank Maintenance, Evolving Planar Maxima, and Selection under Drifting Fitness
Jun 12, 2026Faruk Alpay, Levent SariogluPairwise Comparison Evolutionary Optimization
Department of Computer Engineering, Bahçeşehir University, Istanbul, Turkey
Directing Open-Ended Evolution in Artificial Life via Multi-Scale Path Divergence
Jun 12, 2026Mikhail Akhtyrchenko, Mikhail I. Katsnelson, Andrey UstyuzhaninArtificial Life Evolutionary Optimization
1Constructor University, Bremen, Germany. · 2Constructor Knowledge Labs, Bremen, Germany. · Institute for Molecules and Materials, Radboud University, Nijmegen, Netherlands. +1
ZIVARI-TLBO: A Zero-Cost Inter-Group Evaluated-Elite Relay Mechanism for Teaching-Learning-Based Optimization
Jun 12, 2026Pezhman ZivariEvolutionary Optimization Metaheuristic Optimization
Independent Researcher, Istanbul, Türkiye

Jul 6, 2026, cs.NEJ/K move · Enter open · S save

LLM-Driven Evolutionary Generation of Multi-Objective Bayesian Optimization Algorithms

Georgios Laskaris, Reuben Brasher, Niki van Stein, Elena Raponi+2

Terra Quantum AG, Kornhausstrasse 25, 9000 St. Gallen, Switzerland · LIACS, Leiden University, Leiden, Netherlands

Automated Algorithm Discovery Evolutionary Optimization Bayesian Optimization Large Language Model-Guided Optimization

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Designing effective multi-objective Bayesian optimization (MOBO) algorithms requires balancing many interdependent design choices whose optimal configuration is problem-dependent and typically demands deep expertise. We extend the LLaMEA framework to MOBO, using large language models as mutation and crossover operators within evolutionary strategies to generate complete algorithm implementations, with SMAC hyperparameter optimization integrated into the evolutionary loop. Across nine evolutionary runs we generated approximately 900 algorithms and benchmarked them on twelve synthetic problems (ZDT, DTLZ, WFG) and three real-world engineering problems (RE), using a BoFire qParEGO implementation as a state-of-the-art Bayesian-optimization baseline. On the synthetic suite the strongest generated algorithm attains the highest mean normalized hypervolume (0.971, vs. 0.869 for qParEGO) while requiring roughly 60x less wall-clock time; a Friedman test with post-hoc analysis places the two in a single top-performing group, and per-problem tests find the generated algorithm significantly better than qParEGO on 7 of the 12 problems and never worse, matching state-of-the-art accuracy at an order-of-magnitude lower cost. On the three unseen real-world engineering problems a generated algorithm attains the best mean normalized hypervolume (0.985, vs. 0.971 for qParEGO)--significantly better than qParEGO on two of the three problems--at roughly 3.4x lower wall-clock cost, confirming that the gains transfer beyond the synthetic regime. LLM-driven evolutionary search can thus discover algorithm designs that achieve Pareto-efficient trade-offs difficult to reach through manual design.

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