The GOP Primal — Relaxed Dual Decomposition Approach : Theory

2000 ◽  
pp. 67-139
Author(s):  
Christodoulos A. Floudas
Keyword(s):  
Dual Decomposition ◽  
Decomposition Approach ◽  
Approach Theory

Nonlinear distributed model predictive control for complex systems: application for hydraulic system

2018 ◽  
Vol 41 (10) ◽  
pp. 2751-2763 ◽  
Author(s):  
Nadia Hajji ◽  
Saber Maraoui ◽  
Larbi Chrifi-Alaoui ◽  
Kais Bouzrara
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hydraulic System ◽  
Water Levels ◽  
Distributed Model ◽  
Dual Decomposition ◽  
Decomposition Approach ◽  
Distributed Model Predictive Control ◽  
Nonlinear Predictive Control ◽  
Tank System

In this paper, a nonlinear distributed model predictive control based on dual decomposition approach is proposed for complex system. The global system can be decomposed into several subsystems and each one will be managed by its own controller. To design the nonlinear predictive control in a distributed fashion, an analytical solution is proposed. The latter is based on the approximation of the error using its expansion of Taylor series. The proposed approach is implemented on the three tank system to control the water levels. Simulation results demonstrate the effectiveness of the proposed approach.

scholarly journals An Improved Decomposition Approach and its Computational Technique for Analyzing Primal-Dual Relationship in LP & LFP Problems

2014 ◽  
Vol 33 ◽  
pp. 65-75
Author(s):  
HK Das ◽  
M Babul Hasan
Keyword(s):  
Computational Technique ◽  
Dual Decomposition ◽  
Linear Fractional Programming ◽  
Decomposition Approach ◽  
Dual Approach ◽  
Numerical Examples ◽  
Primal Dual ◽  
Primal And Dual ◽  
Relationship Of ◽  
The Relationship

In this paper, we study the methodology of primal dual solutions in Linear Programming (LP) & Linear Fractional Programming (LFP) problems. A comparative study is also made on different duals of LP & LFP. We then develop an improved decomposition approach for showing the relationship of primal and dual approach of LP & LFP problems by giving algorithm. Numerical examples are given to demonstrate our method. A computer programming code is also developed for showing primal and dual decomposition approach of LP & LFP with proper instructions using AMPL. Finally, we have drawn a conclusion stating the privilege of our method of computation. GANIT J. Bangladesh Math. Soc. Vol. 33 (2013) 65-75 DOI: http://dx.doi.org/10.3329/ganit.v33i0.17660

scholarly journals Simultaneous gene finding in multiple genomes

2015 ◽  
Author(s):  
Stefanie König ◽  
Lars Romoth ◽  
Lizzy Gerischer ◽  
Mario Stanke
Keyword(s):  
Genome Alignment ◽  
Whole Genome ◽  
Gene Finding ◽  
Dual Decomposition ◽  
Closely Related Species ◽  
Protein Coding ◽  
Decomposition Approach ◽  
New Approach ◽  
Gene Structures ◽  
Gains And Losses

As whole genome sequencing is taking on ever-increasing dimensions, the new challenge is the accurate and consistent annotation of entire clades of genomes. We address this problem with a new approach to comparative gene finding that takes a multiple genome alignment of closely related species and simultaneously predicts the location and structure of protein-coding genes in all input genomes, thereby exploiting negative selection and sequence conservation. The model prefers potential gene structures in the different genomes that are in agreement with each other, or – if not – where the exon gains and losses are plausible given the species tree. We formulate the multi-species gene finding problem as a binary labeling problem on a graph. The resulting optimization problem is NP hard, but can be efficiently approximated using a subgradient-based dual decomposition approach. The proposed method was tested on a whole-genome alignment of 12 Drosophila species and its accuracy evaluated on D. melanogaster. The method is being implemented as an extension to the gene finder AUGUSTUS.

A Hybrid Meta-Heuristic Algorithm for Dynamic Spectrum Management in Multiuser Systems

2011 ◽  
Vol 2 (4) ◽  
pp. 29-40
Author(s):  
Hernan X. Cordova ◽  
Leo Van Biesen
Keyword(s):  
Electromagnetic Coupling ◽  
Spectrum Management ◽  
Global Optimum ◽  
Dynamic Spectrum ◽  
Convergence Time ◽  
Digital Subscriber Line ◽  
Dual Decomposition ◽  
Decomposition Approach ◽  
Dynamic Spectrum Management ◽  
Cable Bundle

One of the major sources of performance degradation of current Digital Subscriber Line systems is the electromagnetic coupling among different twisted pairs within the same cable bundle (crosstalk). Several algorithms for Dynamic Spectrum management have been proposed to counteract the crosstalk effect but their complexity remains a challenge in practice. Optimal Spectrum Balancing (OSB) is a centralized algorithm that optimally allocates the available transmit power over the tones making use of a Dual decomposition approach where Lagrange multipliers are used to enforce the constraints and decouple the problem over the tones. However, the overall complexity of this algorithm remains a challenge for practical DSL environments. The authors propose a low-complex algorithm based on a combination of simulated annealing and non-linear simplex to find local (almost global) optimum spectra for multiuser DSL systems, whilst significantly reducing the prohibitive complexity of traditional OSB. The algorithm assumes a Spectrum Management Center (at the cabinet side) but it neither relies on own end-user modem calculations nor on messaging-passing for achieving its performance objective. The approach allows furthering reducing the number of function evaluations achieving further reduction on the convergence time (up to ~27% gain) at reasonable payoff (weighted data rate sum).

A Dual Decomposition Approach to Feature Correspondence

2013 ◽  
Vol 35 (2) ◽  
pp. 259-271 ◽  
Author(s):  
Lorenzo Torresani ◽  
Vladimir Kolmogorov ◽  
Carsten Rother
Keyword(s):  
Dual Decomposition ◽  
Feature Correspondence ◽  
Decomposition Approach

scholarly journals Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Khush Bakht ◽  
Furqan Jameel ◽  
Zain Ali ◽  
Wali Ullah Khan ◽  
Imran Khan ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Cognitive Radios ◽  
Limiting Factors ◽  
Dual Decomposition ◽  
Joint Power ◽  
Decomposition Approach ◽  
Spectrum Scarcity ◽  
The Individual

The issue of spectrum scarcity in wireless networks is becoming prominent and critical with each passing year. Although several promising solutions have been proposed to provide a solution to spectrum scarcity, most of them have many associated tradeoffs. In this context, one of the emerging ideas relates to the utilization of cognitive radios (CR) for future heterogeneous networks (HetNets). This paper provides a marriage of two promising candidates (i.e., CR and HetNets) for beyond fifth generation (5G) wireless networks. More specifically, a joint power allocation and user assignment solution for the multiuser underlay CR-based HetNets has been proposed and evaluated. To counter the limiting factors in these networks, the individual power of transmitting nodes and interference temperature protection constraints of the primary networks have been considered. An efficient solution is designed from the dual decomposition approach, where the optimal user assignment is obtained for the optimized power allocation at each node. The simulation results validate the superiority of the proposed optimization scheme against conventional baseline techniques.

A Hybrid Meta-Heuristic Algorithm for Dynamic Spectrum Management in Multiuser Systems

2012 ◽  
pp. 32-43
Author(s):  
Hernan X. Cordova ◽  
Leo Van Biesen
Keyword(s):  
Electromagnetic Coupling ◽  
Spectrum Management ◽  
Global Optimum ◽  
Dynamic Spectrum ◽  
Convergence Time ◽  
Digital Subscriber Line ◽  
Dual Decomposition ◽  
Decomposition Approach ◽  
Dynamic Spectrum Management ◽  
Cable Bundle

One of the major sources of performance degradation of current Digital Subscriber Line systems is the electromagnetic coupling among different twisted pairs within the same cable bundle (crosstalk). Several algorithms for Dynamic Spectrum management have been proposed to counteract the crosstalk effect but their complexity remains a challenge in practice. Optimal Spectrum Balancing (OSB) is a centralized algorithm that optimally allocates the available transmit power over the tones making use of a Dual decomposition approach where Lagrange multipliers are used to enforce the constraints and decouple the problem over the tones. However, the overall complexity of this algorithm remains a challenge for practical DSL environments. The authors propose a low-complex algorithm based on a combination of simulated annealing and non-linear simplex to find local (almost global) optimum spectra for multiuser DSL systems, whilst significantly reducing the prohibitive complexity of traditional OSB. The algorithm assumes a Spectrum Management Center (at the cabinet side) but it neither relies on own end-user modem calculations nor on messaging-passing for achieving its performance objective. The approach allows furthering reducing the number of function evaluations achieving further reduction on the convergence time (up to ~27% gain) at reasonable payoff (weighted data rate sum).

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