RoverDevKit is an open physics-based evaluator for lunar micro-rover conceptual design that runs in 30 ms and uses NSGA-II to identify mission-dependent optimal wheel configurations and binding trades.
A fast and elitistmultiobjectivegeneticalgorithm:NSGA-II
39 Pith papers cite this work, alongside 47,759 external citations. Polarity classification is still indexing.
39
Pith papers citing it
47.8k
external citations · external index
citation-role summary
background 2
baseline 1
method 1
citation-polarity summary
representative citing papers
A co-evolutionary method evolves LLM prompts and circuits to produce 8-bit approximate multipliers with better error-area trade-offs than EvoApproxLib.
COTHROM applies a Potts Hamiltonian representation of constitutional mandates, MCMC/simulated annealing optimization, and Pareto/MCDA analysis to improve Irish constituency boundaries over existing legal ones in County Cork for proportionality and compactness across weightings.
A U-Net surrogate with multigroup attention pooling is trained on OpenMC sensitivity data and combined with gradient optimization to generate grid-based critical experiment geometries that achieve c_k values up to 0.97757 for HALEU fuel validation.
An optimization-based inverse design method discovers metainterfaces achieving custom friction laws including power laws with exponents from 2/3 to 1.35 and bilinear forms, with experimental validation for some cases.
LLMForge is a NAS framework with Infinite-Head Attention, a Forge-Former surrogate, and Forge-DSE engine that discovers hardware-specific architectures for edge language models, yielding variants with improved accuracy, energy, or latency on different substrates.
DRSR uses Quality-Diversity to produce diverse symbolic regression expressions differing in residual distributions, enabling post-search selection on synthetic and astronomical data.
DIPS fine-tunes LLMs to output ordered feasible decision vectors approximating Pareto fronts for constrained bi-objective convex problems, reaching 95-98% normalized hypervolume with 0.16s inference.
EvoPref applies NSGA-II evolutionary optimization with archive-based diversity to populations of LoRA adapters, yielding 18% higher preference coverage and 47% lower collapse than gradient descent baselines while matching alignment quality.
A homotopy-plus-MCMC data-generation pipeline trains a mass-conditioned diffusion model that yields 40% more feasible initial costates and a better Pareto front for multiobjective indirect low-thrust transfers than adjoint-control-transformation baselines.
GLUE orchestrates frozen pre-trained generative models into a system-level design generator that enforces feasibility, performance, and diversity, with data-driven and data-free variants benchmarked on UAV design.
Brush is a new symbolic regression method that integrates tree-like rules with function optimization, matching or beating decision trees and forests on clinical scoring tasks while producing simpler interpretable models.
A genetic algorithm optimizes weighted combinations of LLM-perceived harm mitigation, expert costs, and participatory scores over stakeholder-action pairs to surface viable AI policy packages for media harms.
Equal reward weighting outperforms targeted weighting in RL-based BPMN generation across 48 configurations, with design choices producing effects as large as applying RL itself.
PGDS is a new explainable AI method for many-objective optimization that automates target selection via partitioning and identifies influential decision variables through distance-based sensitivity analysis.
A methodology is proposed to integrate Life Cycle Assessment as an additional discipline in Multidisciplinary Design Analysis and Optimization frameworks for launch vehicle eco-design, demonstrated through multi-objective optimization on an expendable launcher.
TCP-MCP co-evolves prompts and topologies for multi-agent systems, reporting 82.66-96.61% accuracy on MMLU-Pro/MMLU/GSM8K while using up to 5.69x fewer tokens than debate baselines.
Develops a posterior-informed two-stage stochastic multi-objective optimization framework for exploration well portfolio selection under uncertainty, solved via sample average approximation and NSGA-II.
P-GONE applies generative ML to optimize Trotter-Suzuki decompositions, reporting up to 19.4x circuit depth reduction at F >= 0.95 versus Qiskit baselines on structured Hamiltonians.
Surrogate-assisted neuroevolution produces Pareto-optimal chlorine dosing policies for water distribution systems that outperform PPO on four practical objectives.
CoCoMagic applies constrained cooperative co-evolution to metamorphic and differential testing to find up to 287% more distinct behavioral divergences in an end-to-end ADS than baseline search methods.
CHAMB-GA is a containerized microservice framework that scales genetic algorithms from laptops to 3,500+ cores on Kubernetes and SLURM with low overhead.
Describes an LLM-orchestrated workflow that trains a surrogate on CAE data (R²=0.87), runs NSGA-II optimization, generates morphed geometries, and produces 35 compliant pedestrian-protection designs in a front-bumper case study.
A framework repairs CPS requirements in Simulink by leveraging system execution data and is evaluated as effective on six real-world case studies covering 12 requirements.
citing papers explorer
-
Asteroid Mining to Sustain a Mars Colony: A Logistics Point of View
Optimized trajectories allow asteroid mining to supply metals for Mars habitats and rovers, potentially enabling sustainable colonies.