On q-steepest descent method for unconstrained multiobjective optimization problems
Por um escritor misterioso
Last updated 16 junho 2024
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.
SciELO - Brasil - A SURVEY ON MULTIOBJECTIVE DESCENT METHODS A SURVEY ON MULTIOBJECTIVE DESCENT METHODS
PDF) On q-BFGS algorithm for unconstrained optimization problems
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization - ScienceDirect
Unconstrained Optimization Problem - ppt video online download
Chapter 4 Line Search Descent Methods Introduction to Mathematical Optimization
Unconstrained Nonlinear Optimization Algorithms - MATLAB & Simulink
Accelerated Diagonal Steepest Descent Method for Unconstrained Multiobjective Optimization
Full article: An incremental descent method for multi-objective optimization
Introduction to Optimization Constraints with SciPy, by Nicolo Cosimo Albanese
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