Results 41 to 50 of about 14,697 (286)
Operations Research PerspectivesThis paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted
Sona Babu, B.S. Girish
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Improving Pareto Front Learning via Multi-Sample Hypernetworks
, 2023 Pareto Front Learning (PFL) was recently introduced as an effective approach to obtain a mapping function from a given trade-off vector to a solution on the Pareto front, which solves the multi-objective optimization (MOO) problem.
Hoang, Long P. +3 more
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FEBS Open Bio, EarlyView.Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman +4 more
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Learning and Selection of Pareto Optimal Policies Matching User Preferences
IEEE AccessReinforcement learning, which is attracting attention as a method for optimizing sequential decision-making, primarily focuses on scenarios with a single objective.
Akinori Tamura, Sachiyo Arai
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Multi-Objective Feature Selection Method Based on Hybrid MI and PSO Algorithm
Jisuanji kexue yu tansuo, 2020 Feature selection is an important pre-processing in data mining, due to a lot of redundant and irrelevant features in datasets. A filter-wrapper multi-objective feature selection method based on hybrid mutual information and particle swarm optimization ...
WANG Jinjie, LI Wei
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Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
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Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
International Journal of Forestry Research, 2012 A stand-level, multiobjective evolutionary algorithm (MOEA) for determining a set of efficient thinning regimes satisfying two objectives, that is, value production for sawlog harvesting and volume production for a pulpwood market, was successfully ...
Oliver Chikumbo
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Advanced Robotics Research, EarlyView.A codesign multiobjective optimization framework was developed to enhance the morphology and controller of a snake‐like robot driven by artificial muscles. It improved planar locomotion, agility, and power efficiency. The approach optimized link geometry and controller gains, revealing that shorter muscles near joints and longer linkages maximize ...
Ayla Valles, Mahdi Haghshenas‐Jaryani
wiley +1 more source