Search results for "Particle swarm optimization"

Memetic Algorithms in Engineering and Design

2012

When dealing with real-world applications, one often faces non-linear and nondifferentiable optimization problems which do not allow the employment of exact methods. In addition, as highlighted in [104], popular local search methods (e.g. Hooke-Jeeves, Nelder Mead and Rosenbrock) can be ill-suited when the real-world problem is characterized by a complex and highly multi-modal fitness landscape since they tend to converge to local optima. In these situations, population based meta-heuristics can be a reasonable choice, since they have a good potential in detecting high quality solutions. For these reasons, meta-heuristics, such as Genetic Algorithms (GAs), Evolution Strategy (ES), Particle …

Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods

2018

Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively direct the solution process. However, when analyzing the performance of these methods, a critical issue is how to systematically involve decision makers. A recent approach to this problem is to replace a decision maker with an artificial one to be able to systematically evaluate and compare reference point based interactive methods in controlled experiments. In this study, a new artificial decision maker is proposed, which reuses the dynamics of particle swarm optimization f…

Training Artificial Neural Networks With Improved Particle Swarm Optimization

2020

Particle Swarm Optimization (PSO) is popular for solving complex optimization problems. However, it easily traps in local minima. Authors modify the traditional PSO algorithm by adding an extra step called PSO-Shock. The PSO-Shock algorithm initiates similar to the PSO algorithm. Once it traps in a local minimum, it is detected by counting stall generations. When stall generation accumulates to a prespecified value, particles are perturbed. This helps particles to find better solutions than the current local minimum they found. The behavior of PSO-Shock algorithm is studied using a known: Schwefel's function. With promising performance on the Schwefel's function, PSO-Shock algorithm is util…

Fault-Tolerant Application Mapping on to ZMesh topology based Network-on-Chip Design

2020

This paper proposes Particle Swarm Optimization (PSO) based fault-tolerant application mapping on to ZMesh topology based Network-on-Chip (NoC) design. Permanent faults in application cores has been considered and performed application mapping using PSO. The major contribution of this paper is to find out the best position for the spare core to be placed in the network using PSO. Experimentations have been carried out by scaling the ZMesh network size and percentage of network faults. The results show that the proposed approach leads to minimum overhead in communication cost over fault-free result.

Target 5G visible light positioning signal subcarrier extraction method using particle swarm optimization algorithm

2021

International audience; With the explosive growth of demand for Internet of Things (IoT) applications and the increasing dependence of users on wireless connections, indoor location based service(LBS) under 5G-Public-Private Partnership (5G-PPP) using cases have received more attention and get rapid development. Thanks to the safty, security and customization of 5G network pointed by 5G forum white paper, indoor positioning systems using unified 5G New Radio (NR) signals have become the focus of the next generation of visible light positioning (VLP) systems. In 5G New Radio(NR) frame, totally 192 subcarriers are used to carry positioning reference signal(PRS). In order to improve the positi…

A computational proposal for a robust estimation of the Pareto tail index: An application to emerging markets

2022

Abstract In this work, we backtest and compare, under the VaR risk measure, the fitting performances of three classes of density distributions (Gaussian, Stable and Pareto) with respect to three different types of emerging markets: Egypt, Qatar and Mexico. We also propose a new technique for the estimation of the Pareto tail index by means of the Threshold Accepting (TAVaR) and the Hybrid Particle Swarm Optimization algorithm (H-PSOVaR). Furthermore, we test the accuracy and robustness of our estimates demonstrating the effectiveness of the proposed approach.

Coupled experiment/simulation approach for the design of radiation-hardened rare-earth doped optical fibers and amplifiers

2011

We developed an approach to design radiation-hardened rare earth -doped fibers and amplifiers. This methodology combines testing experiments on these devices with particle swarm optimization (PSO) calculations. The composition of Er/Yb-doped phosphosilicate fibers was improved by introducing Cerium inside their cores. Such composition strongly reduces the amplifier radiation sensitivity, limiting its degradation: we observed a gain decreasing from 19 dB to 18 dB after 50 krad whereas previous studies reported higher degradations up to 0°dB at such doses. PSO calculations, taking only into account the radiation effects on the absorption efficiency around the pump and emission wavelengths, co…

2014

This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs). Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization) algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifica…

Wireless sensor network coverage problem using modified fireworks algorithm

2016

Wireless sensor networks are emerging technology with increasing number of applications, and consequently an active research area. One of the problems pertinent to wireless sensor networks is the coverage problem with number of definitions, depending on the assumed conditions. In this paper we consider hard optimization area coverage problem with the goal of finding optimal sensor nodes positions that maximize probabilistic coverage of the area of interest. For such type of optimization problem swarm intelligence stochastic metaheuristics have been successfully used. In this paper we propose a modified enhanced fireworks algorithm for wireless sensor network coverage problem and compare it …

Solving a continuous periodic review inventory-location allocation problem in vendor-buyer supply chain under uncertainty

2019

In this work, a mixed-integer binary non-linear two-echelon inventory problem is formulated for a vendor-buyer supply chain network in which lead times are constant and the demands of buyers follow a normal distribution. In this formulation, the problem is a combination of an (r, Q) and periodic review policies based on which an order of size Q is placed by a buyer in each fixed period once his/her on hand inventory reaches the reorder point r in that period. The constraints are the vendors’ warehouse spaces, production restrictions, and total budget. The aim is to find the optimal order quantities of the buyers placed for each vendor in each period alongside the optimal placement of the ve…