Results 41 to 50 of about 190,364 (297)

Directional Pareto Front and Its Estimation to Encourage Multi-Objective Decision-Making

IEEE Access, 2023
This work introduces the following concepts of directional and estimated directional Pareto front to encourage multi-objective decision making, especially when the Pareto front exists in limited regions in the objective space. The general output of multi-
Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato   +2 more
doaj   +1 more source

Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity

Advanced Functional Materials, EarlyView.
Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen, Zheyuan Miao, Gary Tom, Austin H. Cheng, Elizaveta Gusarova, Benjamen Zondag, Tianyi Wu, Dianoosh Kalhori, Boris Hinz, Milad Abolhasani, Alán Aspuru‐Guzik, Eugenia Kumacheva   +11 more
wiley   +1 more source

Set of Pareto solutions for optimum cascade problems using MOPSO algorithm

Results in Engineering, 2022
The MOPSO approach was used to find the Pareto optimal set of the best cascade parameters. To achieve a desired concentration at the waste and product streams, using mass material balance, the objective functions were to reduce the number of machines and
H. Kargaran, S. Yazdani
doaj   +1 more source

An evaluation of best compromise search in graphs [PDF]

, 2013
This work evaluates two different approaches for multicriteria graph search problems using compromise preferences. This approach focuses search on a single solution that represents a balanced tradeoff between objectives, rather than on the whole set ...
Galand, Lucie, Machuca, Enrique, Mandow-Andaluz, Lorenzo   +2 more
core   +4 more sources

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

OPTIMIZATION OF THE PROBLEM SOLVING WITH LIMITED RESOURCE

Доклады Белорусского государственного университета информатики и радиоэлектроники, 2019
The knapsack problem is analyzed on the basis of the mathematical model, which uses the means of multicriterial optimization. The method which defines possible redundancy of the initial data set is offered for the problem. The algorithm of the transition
S. V. Chebakov, L. V. Serebryanaya
doaj  

Construction of Generating Feasible Subsets in the Knapsack Problem

Доклады Белорусского государственного университета информатики и радиоэлектроники
A method for constructing a group of generating feasible subsets in the knapsack problem under the condition that the non-dominance depth of a given Pareto layer is greater than zero is developed.
S. V. Chebakov, L. V. Serebryanaya
doaj   +1 more source

Pareto dominance-based MOEAs on problems with difficult pareto set topologies

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018
Despite the extensive application of multi-objective evolutionary algorithms (MOEAs) to solve multi-objective optimization problems (MOPs), understanding their working principles is still open to research. One of the most popular and successful MOEA approaches is based on Pareto dominance and its relaxed version, Pareto epsilon-dominance. However, such
Marca, Yuri, Aguirre, Hernan, Zapotecas-Martínez, Saúl, Liefooghe, Arnaud, Verel, Sébastien, Derbel, Bilel, Tanaka, Kiyoshi   +6 more
openaire   +2 more sources

Multiobjective Codesign Optimization of a Planar Pneumatic Artificial Muscle‐Based Snake‐Like Robot for Enhanced Agility and Energy Efficiency

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