Proceedings ArticleDOI
Metaheuristic Optimization of Decoupling Capacitors in a Power Delivery Network
Reads0
Chats0
TLDR
In this paper, a metaheuristic technique based generic framework for decoupling capacitor optimization in a practical power delivery network is presented, where the cumulative impedance of a power delivery system is minimized below the target impedance by optimal selection and placement of decoupled capacitors using state-of-the-art meta-heuristic algorithms.Abstract:
In VLSI circuits and systems, it is a common practice to reduce power supply noise in power delivery networks by decoupling capacitors. The optimal selection and placement of decoupling capacitors is crucial for maintaining power integrity efficiently. This paper presents a metaheuristic technique based generic framework for decoupling capacitor optimization in a practical power delivery network. The cumulative impedance of a power delivery network is minimized below the target impedance by optimal selection and placement of decoupling capacitors using state-of-the-art metaheuristic algorithms. A comparative analysis of the performance of these algorithms is presented with the insights of practical implementation.read more
Citations
More filters
Proceedings ArticleDOI
A Machine Learning based Metaheuristic Technique for Decoupling Capacitor Optimization
TL;DR: In this article , an efficient and fast Machine Learning (ML) based surrogate-assisted metaheuristic approach is proposed for the decoupling capacitor optimization problem to reduce the cumulative impedance of the PDN below the target impedance.
Journal ArticleDOI
A Radial Basis Function Network-Based Surrogate-Assisted Swarm Intelligence Approach for Fast Optimization of Power Delivery Networks
TL;DR: In this article , a novel approach using surrogate assisted swarm intelligence is presented for efficient and fast optimization of power delivery networks, where the decoupling capacitors are selected and placed optimally, eventually reducing the cumulative impedance of the PDN below the target impedance.
Journal ArticleDOI
Large-Scale Optimization of Decoupling Capacitors Using Adaptive Region Based Encoding Scheme in Particle Swarm Optimization
TL;DR: In this paper , a novel approach using the Social-Learning Particle Swarm Optimization (SLPSO) technique along with Adaptive Region Search (ARS) is used to tackle the Large-Scale Optimization Problem (LSOP) of decoupling capacitor placement.
References
More filters
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.