Additional information
| Author(s) | Pop, Petrică Claudiu |
|---|
Approximation results for the generalized minimum spanning tree problem
We consider the Generalized Minimum Spanning Tree problem denoted by GMST. It is known that the GMST problem is NP-hard. Throughout this paper we distinguish between so-called positive results and negative in the area of approximation theory. We present an in-approximability result for the GMST problem and under special assumptions we give an approximation algorithm for the problem.
Related products
Recently posted
-
Approximate Solutions for Multi-Objective Optimization Problems via Scalarizing and Nonscalarizing Methods
-
A product of strongly quasi-nonexpansive mappings in Hadamard spaces
-
Inertial viscosity fixed point algorithms for monotone inclusion, convex minimization, and image restoration problems
-
Holderian Stability for Parametric Optimization Models and Applications
-
A Novel Fixed-Point Based Two-Step Inertial Algorithm for Convex Bilevel Optimization in Deep Learning Data Classification
-
Double-step inertial algorithms for equilibrium and fixed point problems in Hilbert spaces
-
Accelerated forward-backward algorithm based on inertial and correction terms with linesearch for solving convex minimization problem and its application
-
A Dual-Projective Double Inertial Forward-Backward Splitting Algorithm for Variational Inclusion Problems with Applications to External Validation in Breast Cancer Diagnosis
-
Efficient Large-Scale Classification with Linex Least Square Twin Bounded Support Vector Machine
-
Classifying compressive strength of clay bricks using an inertial projected forward-backward algorithm