Results 81 to 90 of about 1,432,311 (298)

Distilling the Pareto Optimal Front into Actionable Insights

Environmental Modelling & Software
Abstract Multi-objective optimization (MOO) is becoming increasingly important in environmental decision making, but interpreting highly-dimensional Pareto optimal data often constitutes a cognitive overload for both scientists and stakeholders. To address this challenge, we present PyretoClustR, a modular framework for post-processing Pareto optimal ...
White, Sydney E., Witing, Felix, Wittekind, Cordula, Volk, Martin, Strauch, Michael   +4 more
openaire   +2 more sources

Multiobjective Test Problems with Degenerate Pareto Fronts

CoRR, 2018
In multiobjective optimisation, a set of scalable test problems with a variety of features allow researchers to investigate and evaluate the abilities of different optimisation algorithms, and thus can help them to design and develop more effective and efficient approaches.
Liangli Zhen, Miqing Li, Ran Cheng 0004, Dezhong Peng, Xin Yao 0001   +4 more
openaire   +2 more sources

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

Meta-Modeling by Symbolic Regression and Pareto Simulated Annealing [PDF]

The subject of this paper is a new approach to Symbolic Regression.Other publications on Symbolic Regression use Genetic Programming.This paper describes an alternative method based on Pareto Simulated Annealing.Our method is based on linear regression ...
Teeuwen, G.J.A., Rennen, G., Stinstra, E.   +2 more
core  

Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors

Advanced Science, EarlyView.
This work presents self‐adhesive, stretchable epidermal electrodes and sensors developed through a data‐driven design framework that integrates artificial neural networks with genetic algorithms. By tailoring optimization objectives, either maximizing electrical conductivity and adhesion or enhancing piezoresistive sensitivity, the study enables the ...
Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu   +10 more
wiley   +1 more source

Method of Feasible Directions with Hit-and-Run Sampling for Solving Linearly Constrained Multi-Objective Optimization Problems

Journal of Optimization, Differential Equations and Their Applications
This paper proposes an extension of Zoutendijk’s Method of Feasible Directions (MFD) for solving linearly constrained multi-objective optimization problems.
Ramdani Zoubir, Addoune Smail, Brahmi Boualem   +2 more
doaj   +1 more source

Adaptive Multiswarm Comprehensive Learning Particle Swarm Optimization

Information, 2018
Multiswarm comprehensive learning particle swarm optimization (MSCLPSO) is a multiobjective metaheuristic recently proposed by the authors. MSCLPSO uses multiple swarms of particles and externally stores elitists that are nondominated solutions found so ...
Xiang Yu, Claudio Estevez
doaj   +1 more source

Efficient Pareto-improving Processes [PDF]

We give two procedures for determining whether efficient Pareto improving local changes are possible. When they are, the procedures compute for them. Any procedure generating efficient and Pareto improving changes can be replicated by these procedures ...
Kwan Koo Yun
core  

Pareto-front shape in multiobservable quantum control

, 2017
Many scenarios in the sciences and engineering require simultaneous optimization of multiple objective functions, which are usually conflicting or competing.
Re-Bing Wu, Qiuyang Sun, Sun, Qiuyang, Rabitz, Herschel, Wu, Re-Bing, Herschel Rabitz   +5 more
core   +1 more source

Inverse Design of Pre‐Strain via a Predictive Electromechanical Model for Enhanced Strain Sensing

Advanced Science, EarlyView.
An analytical electromechanical model rooted in microcrack evolution mechanics is globally calibrated from only eight pre‐strain datasets, enabling prediction of the complete sensing response at untested pre‐strain values within the calibrated design space (R2 > 0.99).
Jia‐Chen Shang, Rui Wang, Bo Lu, Ming‐Liang Song, Yu‐Yi Chen, Kuo Han, Xin‐Jie Feng, Bin Sun, Yao‐Guang Cao, Xiao‐Yu Yan, Shi‐Chun Yang   +10 more
wiley   +1 more source