Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Solving polyhedral d.c. optimization problems via concave minimization
View through CrossRef
AbstractThe problem of minimizing the difference of two convex functions is called polyhedral d.c. optimization problem if at least one of the two component functions is polyhedral. We characterize the existence of global optimal solutions of polyhedral d.c. optimization problems. This result is used to show that, whenever the existence of an optimal solution can be certified, polyhedral d.c. optimization problems can be solved by certain concave minimization algorithms. No further assumptions are necessary in case of the first component being polyhedral and just some mild assumptions to the first component are required for the case where the second component is polyhedral. In case of both component functions being polyhedral, we obtain a primal and dual existence test and a primal and dual solution procedure. Numerical examples are discussed.
Springer Science and Business Media LLC
Title: Solving polyhedral d.c. optimization problems via concave minimization
Description:
AbstractThe problem of minimizing the difference of two convex functions is called polyhedral d.
c.
optimization problem if at least one of the two component functions is polyhedral.
We characterize the existence of global optimal solutions of polyhedral d.
c.
optimization problems.
This result is used to show that, whenever the existence of an optimal solution can be certified, polyhedral d.
c.
optimization problems can be solved by certain concave minimization algorithms.
No further assumptions are necessary in case of the first component being polyhedral and just some mild assumptions to the first component are required for the case where the second component is polyhedral.
In case of both component functions being polyhedral, we obtain a primal and dual existence test and a primal and dual solution procedure.
Numerical examples are discussed.
Related Results
Analisis Kebutuhan Modul Matematika untuk Meningkatkan Kemampuan Pemecahan Masalah Siswa SMP N 4 Batang
Analisis Kebutuhan Modul Matematika untuk Meningkatkan Kemampuan Pemecahan Masalah Siswa SMP N 4 Batang
Pemecahan masalah merupakan suatu usaha untuk menyelesaikan masalah matematika menggunakan pemahaman yang telah dimilikinya. Siswa yang mempunyai kemampuan pemecahan masalah rendah...
Cutting Planes for Low-Rank-Like Concave Minimization Problems
Cutting Planes for Low-Rank-Like Concave Minimization Problems
Concavity cuts play an important role in several algorithms for concave minimization, such as pure cutting plane algorithms, conical algorithms, and branch-and-bound algorithms. Fo...
The mechanisms of minimization: How interrogation tactics suggest lenient sentencing through pragmatic implication
The mechanisms of minimization: How interrogation tactics suggest lenient sentencing through pragmatic implication
Objective: Minimization is a legal interrogation tactic in which an interrogator attempts to decrease a suspect's resistance to confessing by, for example, downplaying the seriousn...
Kemampuan Pemecahan Masalah Dalam Menyelesaikan Soal Volume Kubus
Kemampuan Pemecahan Masalah Dalam Menyelesaikan Soal Volume Kubus
Problem solving ability is an ability that every student should be able to master so that the learning process runs smoothly. In problem solving, students are expected to have the ...
AFFORDANCE BASED FRAMEWORK OF HUMAN PROBLEM SOLVING: A NONREPRESENTATIONAL ALTERNATIVE
AFFORDANCE BASED FRAMEWORK OF HUMAN PROBLEM SOLVING: A NONREPRESENTATIONAL ALTERNATIVE
Problem solving is a crucial higher-order thinking ability of humans. Humans’ ability to solve problems is a critical higher-order thinking ability. Mathematical problem solving, a...
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
The project aims at the design and development of six hybrid nature inspired algorithms based on Grey Wolf Optimization algorithm with Artificial Bee Colony Optimization algorithm ...
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
The project aims at the design and development of six hybrid nature inspired algorithms based on Grey Wolf Optimization algorithm with Artificial Bee Colony Optimization algorithm ...
Canonical Analysis of two Convex Polyhedral Cones and Applications
Canonical Analysis of two Convex Polyhedral Cones and Applications
Canonical analysis of two convex polyhedral cones consists in looking for two vectors (one in each cone) whose square cosine is a maximum. This paper presents new results about the...