Results 91 to 100 of about 2,735,316 (329)
MathematicsDecision-making plays a pivotal role in data-driven optimization, aiming to achieve optimal results by identifying the most effective combination of input variables.
Parastoo Dehnad +2 more
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Public Service System Design With Conflicting Criteria
IEEE Access, 2021 Multi-criteria optimization problems represent a crucial task for any designer of a public service system due to conflicting criteria, which have to be faced.
Jaroslav Janacek, Rene Fabricius
doaj +1 more source
Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy
Advanced Science, EarlyView.A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim +5 more
wiley +1 more source
Self-Evolutionary Optimization for Pareto Front Learning
CoRR, 2021 Multi-task learning (MTL), which aims to improve performance by learning multiple tasks simultaneously, inherently presents an optimization challenge due to multiple objectives. Hence, multi-objective optimization (MOO) approaches have been proposed for multitasking problems. Recent MOO methods approximate multiple optimal solutions (Pareto front) with
Simyung Chang +3 more
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Advanced Science, EarlyView.A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai +3 more
wiley +1 more source
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017 10 pages, accepted at GECCO'17 as a poster paper (2 pages)
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Advanced Science, EarlyView.A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei +7 more
wiley +1 more source
Constructing a Pareto front approximation for decision making [PDF]
Mathematical Methods of Operations Research, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Markus Hartikainen +2 more
openaire +4 more sources
A Generative Neuro‐Symbolic AI for Protein Sequence Design
Advanced Science, EarlyView.We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front
IEEE Transactions on Evolutionary Computation, 2018 The hypervolume and the inverted generational distance (IGD) have been frequently used for the comparison of evolutionary multiobjective optimization algorithms.
H. Ishibuchi +3 more
semanticscholar +1 more source