On q-steepest descent method for unconstrained multiobjective optimization problems
Por um escritor misterioso
Descrição
The <i>q</i>-gradient is the generalization of the gradient based on the <i>q</i>-derivative. The <i>q</i>-version of the steepest descent method for unconstrained multiobjective optimization problems is constructed and recovered to the classical one as <i>q</i> equals 1. In this method, the search process moves step by step from global at the beginning to particularly neighborhood at last. This method does not depend upon a starting point. The proposed algorithm for finding critical points is verified in the numerical examples.
Performance of q-Steepest Descent Method.
20 Best Optimization Books of All Time - BookAuthority
PDF) On q-BFGS algorithm for unconstrained optimization problems
Stabilization of the fluidic pinball with gradient-enriched machine learning control, Journal of Fluid Mechanics
3. Consider the following unconstrained optimization
Accelerated Diagonal Steepest Descent Method for Unconstrained Multiobjective Optimization
Particle Swarm Optimization with a Simplex Strategy to Avoid Getting Stuck on Local Optimum
Equality-Constrained Engineering Design Optimization Using a Novel Inexact Quasi-Newton Method
PDF) Comparison Between Steepest Descent Method and Conjugate Gradient Method by Using Matlab
Accelerated Diagonal Steepest Descent Method for Unconstrained Multiobjective Optimization
Accelerated Diagonal Steepest Descent Method for Unconstrained Multiobjective Optimization
Neural optimization machine: a neural network approach for optimization and its application in additive manufacturing with physics-guided learning
SciELO - Brasil - A SURVEY ON MULTIOBJECTIVE DESCENT METHODS A SURVEY ON MULTIOBJECTIVE DESCENT METHODS
SciELO - Brasil - A SURVEY ON MULTIOBJECTIVE DESCENT METHODS A SURVEY ON MULTIOBJECTIVE DESCENT METHODS
