On q-steepest descent method for unconstrained multiobjective optimization problems

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.

Equality-Constrained Engineering Design Optimization Using a Novel Inexact Quasi-Newton Method

PDF) A Steepest Descent Method for Set Optimization Problems with Set-Valued Mappings of Finite Cardinality

Cooperative and Competitive Multi-Agent Systems: From Optimization to Games

Stabilization of the fluidic pinball with gradient-enriched machine learning control, Journal of Fluid Mechanics

Geometry optimization - Schlegel - 2011 - WIREs Computational Molecular Science - Wiley Online Library

On q-steepest descent method for unconstrained multiobjective optimization problems

Mathematics, Free Full-Text

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Constrained Engineering Optimization Algorithm Based on Elite Selection – topic of research paper in Mathematics. Download scholarly article PDF and read for free on CyberLeninka open science hub.