A brief introduction to manifold optimization
Manifold optimization is ubiquitous in computational and applied mathematics, statistics,
engineering, machine learning, physics, chemistry, etc. One of the main challenges usually …
engineering, machine learning, physics, chemistry, etc. One of the main challenges usually …
A cooperative advertising collaboration policy in supply chain management under uncertain conditions
Many industries are facing big challenges to design supply chains in a way to maximize the
profit and meet the heightened expectations of the customer. This new era entirely relies on …
profit and meet the heightened expectations of the customer. This new era entirely relies on …
E-agricultural supply chain management coupled with blockchain effect and cooperative strategies
The agricultural industry is highly underdeveloped and requires transformation in
technology for food safety and reliability. A digital world is relying on blockchain technology …
technology for food safety and reliability. A digital world is relying on blockchain technology …
Simple algorithms for optimization on Riemannian manifolds with constraints
We consider optimization problems on manifolds with equality and inequality constraints. A
large body of work treats constrained optimization in Euclidean spaces. In this work, we …
large body of work treats constrained optimization in Euclidean spaces. In this work, we …
Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization
In this paper, an inexact proximal-point penalty method is studied for constrained
optimization problems, where the objective function is non-convex, and the constraint …
optimization problems, where the objective function is non-convex, and the constraint …
Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
We analyze worst-case complexity of a Proximal augmented Lagrangian (Proximal AL)
framework for nonconvex optimization with nonlinear equality constraints. When an …
framework for nonconvex optimization with nonlinear equality constraints. When an …
A Newton-CG based augmented Lagrangian method for finding a second-order stationary point of nonconvex equality constrained optimization with complexity …
In this paper we consider finding a second-order stationary point (SOSP) of nonconvex
equality constrained optimization when a nearly feasible point is known. In particular, we first …
equality constrained optimization when a nearly feasible point is known. In particular, we first …
Supply chain modelling of the automobile multi-stage production considering circular economy by waste management using recycling and reworking operations
The supply chain management plays a crucial role in delivering products from a supplier,
through the manufacturer, distributors, and retailers to the targeted customers. The lifecycle …
through the manufacturer, distributors, and retailers to the targeted customers. The lifecycle …
Moreau envelope augmented Lagrangian method for nonconvex optimization with linear constraints
The augmented Lagrangian method (ALM) is one of the most useful methods for constrained
optimization. Its convergence has been well established under convexity assumptions or …
optimization. Its convergence has been well established under convexity assumptions or …
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold
S Schechtman, D Tiapkin… - The Thirty Sixth …, 2023 - proceedings.mlr.press
We consider the problem of minimizing a non-convex function over a smooth manifold M.
We propose a novel algorithm, the Orthogonal Directions Constrained Gradient Method …
We propose a novel algorithm, the Orthogonal Directions Constrained Gradient Method …