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.

Accelerated Diagonal Steepest Descent Method for Unconstrained Multiobjective Optimization

Introducing a novel algorithm for minimum-time low-thrust orbital transfers with free initial condition - I Shafieenejad, AB Novinzadeh, VR Molazadeh, 2015

Restricted-Variance Molecular Geometry Optimization Based on Gradient-Enhanced Kriging

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

A Particle Swarm Optimization Algorithm with Gradient Perturbation and Binary Tree Depth First Search Strategy

Mathematical optimization - Wikiwand

Steepest Descent Method (Unconstrained Optimization)

Energies, Free Full-Text

Frontiers Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning

Solved 2. Steepest descent for unconstrained quadratic

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization 3030429490, 9783030429492

3. Consider the following unconstrained optimization