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Multicriteria Interval Optimization of Conditions for Complex Chemical Reactions Based on a Kinetic Model
AbstractThe problem of multicriteria interval optimization of the conditions for complex chemical reactions is formulated based on an interval...
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Derivative-Free Optimization with Transformed Objective Functions and the Algorithm Based on the Least Frobenius Norm Updating Quadratic Model
Derivative-free optimization (DFO) problems are optimization problems where the derivative information is unavailable. The least Frobenius norm...
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Numerical Investigation of Optimization Algorithms for Adapting the Hydrodynamic Model Based on the Results of Well Tests
AbstractThis study presents a numerical investigation of optimization algorithms for the adaptation of hydrodynamic models based on well test...
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Numerical Algorithm for Source Determination in a Diffusion–Logistic Model from Integral Data Based on Tensor Optimization
AbstractAn algorithm has been developed for numerically solving the source determination problem in the model of information dissemination in...
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Adaptive nonlinear optimization of district heating networks based on model and discretization catalogs
We propose an adaptive optimization algorithm for operating district heating networks in a stationary regime. The behavior of hot water flow in the...
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Teaching–Learning-Based Optimization for Parameter Identification of an Activated Sludge Process Model
AbstractThis paper proposes a recent optimization method called TLBO (teaching–learning-based optimization) to identify the unknown parameters of an...
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Homogenization based topology optimization of fluid-pressure loaded structures using the Biot–Darcy Model
Homogenization method is applied to topology optimization of a weakly coupled two physics problem, where structures are made of periodically...
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Hyperparameter Optimization for Gradient-Boosted Tree-Based Machine Learning Models and Their Effect on Model Performance
Gradient-boosted tree-based machine learning models have several parameters called hyperparameters that control their fit and performance. Several...
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Development of an Agent-Based Optimization Model for the Human Capital Market
The article considers a multi-agent optimization model of human capital markets: education, healthcare, recreation, labor. The agent’s problem of a...
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RETRACTED ARTICLE: Premium rate making of jujube revenue insurance in **njiang Aksu Region based on the mixed Copula-stochastic optimization model
Scientific and reasonable premium rate is the premise to guarantee the high-quality development of agricultural insurance, while unscientific premium...
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Inverse Lighting with Differentiable Physically-Based Model
The design of scene lighting in video games and computer graphics can be a challenging and time-consuming task for lighting artists. Automating the...
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The prediction model of water level in front of the check gate of the LSTM neural network based on AIW-CLPSO
To solve the problem of predicting water level in front of check gate under different time scales, a different time scale prediction model with a...
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A new subspace minimization conjugate gradient method based on conic model for large-scale unconstrained optimization
Conjugate gradient method is one of the most efficient methods for large-scale unconstrained optimization and has attracted focused attention of...
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Heteroscedastic Bayesian optimization using generalized product of experts
In many real world optimization problems observations are corrupted by a heteroscedastic noise, which depends on the input location. Bayesian...
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Exterior-Point Optimization for Sparse and Low-Rank Optimization
Many problems of substantial current interest in machine learning, statistics, and data science can be formulated as sparse and low-rank optimization...
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NeuroPrim: An attention-based model for solving NP-hard spanning tree problems
Spanning tree problems with specialized constraints can be difficult to solve in real-world scenarios, often requiring intricate algorithmic design...
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Model-Based Methods
Model-based methods are often used to impute missing values. If the model assumptions are satisfied, these types of methods are often superior to...
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Motion, Dual Quaternion Optimization and Motion Optimization
We regard a dual quaternion as a real eight-dimensional vector and present a dual quaternion optimization model. Then we introduce motions as real...
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Fixed-Point Methods in Optimization Problems for Control Systems
In this paper, we consider a new approach to optimization of nonlinear control systems based on the representation of optimality conditions and...
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Non-Convex Optimization of Resource Allocation in Fog Computing Using Successive Approximation
Fog computing can deliver low delay and advanced IT services to end users with substantially reduced energy consumption. Nevertheless, with soaring...