scholarly journals Nature–inspired metaheuristic algorithms to find near–OGR sequences for WDM channel allocation and their performance comparison

2017 ◽  
Vol 15 (1) ◽  
pp. 520-547 ◽  
Author(s):  
Shonak Bansal ◽  
Neena Gupta ◽  
Arun Kumar Singh
Keyword(s):  
Wavelength Division Multiplexing ◽  
Channel Allocation ◽  
Statistical Tests ◽  
Optimization Algorithms ◽  
Performance Comparison ◽  
Metaheuristic Algorithms ◽  
Optical Channel ◽  
Complete Problems ◽  
Simulation Results ◽  
Nature Inspired Algorithms

Abstract Nowadays, nature–inspired metaheuristic algorithms are most powerful optimizing algorithms for solving the NP–complete problems. This paper proposes three approaches to find near–optimal Golomb ruler sequences based on nature–inspired algorithms in a reasonable time. The optimal Golomb ruler (OGR) sequences found their application in channel–allocation method that allows suppression of the crosstalk due to four–wave mixing in optical wavelength division multiplexing systems. The simulation results conclude that the proposed nature–inspired metaheuristic optimization algorithms are superior to the existing conventional and nature–inspired algorithms to find near–OGRs in terms of ruler length, total optical channel bandwidth, computation time, and computational complexity. Based on the simulation results, the performance of proposed different nature–inspired metaheuristic algorithms are being compared by using statistical tests. The statistical test results conclude the superiority of the proposed nature–inspired optimization algorithms.

Nature-Inspired-Based Multi-Objective Hybrid Algorithms to Find Near-OGRs for Optical WDM Systems and Their Comparison

2018 ◽  
pp. 175-211 ◽  
Author(s):  
Shonak Bansal
Keyword(s):  
Wavelength Division Multiplexing ◽  
Channel Allocation ◽  
Statistical Tests ◽  
Computation Time ◽  
Wavelength Division ◽  
Multi Objective ◽  
Optical Wdm ◽  
Complete Problems ◽  
Golomb Rulers ◽  
Bandwidth Expansion

Nature-inspired-based approaches are powerful optimizing algorithms to solve the NP-complete problems having multiple objectives. In this chapter, two nature-inspired-based multi-objective optimization algorithms (MOAs) and their hybrid forms are proposed to find the optimal Golomb rulers (OGRs) in a reasonable time. The OGRs can be used as a channel-allocation algorithm that allows suppression of the four-wave mixing crosstalk in optical wavelength division multiplexing systems. The presented results conclude that the proposed MOAs outperforms the existing conventional classical and nature-inspired-based algorithms to find near-OGRs in terms of ruler length, total occupied optical bandwidth, bandwidth expansion factor, computation time, and computational complexity. In order to find the superiority of proposed MOAs, the performances of the proposed algorithms are also analyzed by using statistical tests.

Nature-Inspired-Based Modified Multi-Objective BB-BC Algorithm to Find Near-OGRs for Optical WDM Systems and Its Performance Comparison

2018 ◽  
pp. 1-25 ◽  
Author(s):  
Shonak Bansal ◽  
Kuldeep Sharma
Keyword(s):  
Optimization Algorithm ◽  
Statistical Tests ◽  
Big Bang ◽  
Performance Comparison ◽  
Optical Channel ◽  
Wavelength Division ◽  
Multi Objective ◽  
Optical Wdm ◽  
Golomb Rulers ◽  
Quadratic Congruence

Multi-objective nature-inspired-based approaches are powerful optimizing algorithms to solve the multiple objectives in NP-complete engineering design problems. This chapter proposes a nature-inspired-based modified multi-objective big bang-big crunch (M-MOBB-BC) optimization algorithm to find the Optimal Golomb rulers (OGRs) in a reasonable timeframe. The OGRs have their important application as channel-allocation algorithm that allow suppression of the four-wave mixing crosstalk in optical wavelength division multiplexing systems. The presented simulation results conclude that the proposed hybrid algorithm is superior to the existing conventional classical algorithms, namely extended quadratic congruence and search algorithm and nature-inspired-based algorithms, namely genetic algorithms, biogeography-based optimization, and simple BB-BC optimization algorithm to find near-OGRs in terms of ruler length, total occupied optical channel bandwidth, bandwidth expansion factor, computation time, computational complexity, and non-parametric statistical tests.

scholarly journals GBUO: “The Good, the Bad, and the Ugly” Optimizer

2021 ◽  
Vol 11 (5) ◽  
pp. 2042
Author(s):  
Hadi Givi ◽  
Mohammad Dehghani ◽  
Zeinab Montazeri ◽  
Ruben Morales-Menendez ◽  
Ricardo A. Ramirez-Mendoza ◽  
...  
Keyword(s):  
High Dimension ◽  
Essential Role ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Stochastic Search ◽  
Objective Functions ◽  
Science And Engineering ◽  
Fixed Dimension ◽  
Dimension Functions ◽  
Simulation Results

Optimization problems in various fields of science and engineering should be solved using appropriate methods. Stochastic search-based optimization algorithms are a widely used approach for solving optimization problems. In this paper, a new optimization algorithm called “the good, the bad, and the ugly” optimizer (GBUO) is introduced, based on the effect of three members of the population on the population updates. In the proposed GBUO, the algorithm population moves towards the good member and avoids the bad member. In the proposed algorithm, a new member called ugly member is also introduced, which plays an essential role in updating the population. In a challenging move, the ugly member leads the population to situations contrary to society’s movement. GBUO is mathematically modeled, and its equations are presented. GBUO is implemented on a set of twenty-three standard objective functions to evaluate the proposed optimizer’s performance for solving optimization problems. The mentioned standard objective functions can be classified into three groups: unimodal, multimodal with high-dimension, and multimodal with fixed dimension functions. There was a further analysis carried-out for eight well-known optimization algorithms. The simulation results show that the proposed algorithm has a good performance in solving different optimization problems models and is superior to the mentioned optimization algorithms.

scholarly journals Elephant Herding Optimization for Energy-Based Localization

2018 ◽  
Author(s):  
Sérgio Correia ◽  
Marko Beko ◽  
Luís Cruz ◽  
Slavisa Tomic
Keyword(s):  
Source Localization ◽  
Wireless Sensors ◽  
Performance Comparison ◽  
Sensor Nodes ◽  
Convex Relaxations ◽  
Noisy Environments ◽  
New Approach ◽  
Metaheuristic Methods ◽  
Simulation Results ◽  
First Time

This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations (like all existing approaches do), we here tackle it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics is applied to this type of problems. More specifically an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms the existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.

Design and Simulation of Arrayed Waveguide Grating for Miniature Raman Spectrometer

2014 ◽  
Vol 644-650 ◽  
pp. 3588-3592
Author(s):  
Ying Chao Xu ◽  
Qing Na Wang ◽  
Wen Zhang Zhu
Keyword(s):  
Wavelength Division Multiplexing ◽  
Insertion Loss ◽  
Phase Error ◽  
Optical Channel ◽  
Arrayed Waveguide Grating ◽  
Waveguide Grating ◽  
Raman Spectrometer ◽  
Technical Requirements ◽  
Arrayed Waveguide ◽  
Miniature Raman Spectrometer

Arrayed waveguide grating (AWG) is a very popular dense wavelength division multiplexing (DWDM) device, which is produced in the field of optical communication technology. Instead of traditional grating and lens spectral system, AWG is used as the spectral chip in miniature Raman spectrometer. It’s quite important for miniature Raman spectrometer in miniaturization and low cost. This paper analyzed the basic principles of AWG device, and introduces the insertion loss, crosstalk and phase error performance parameters, also focuses on the specific technical requirements about wavelength, optical channel number, phase error, wavelength resolution and bandwidth, which are applied in miniature Raman spectrometer. Some new researches and a series of related simulation have been made, finally won the 1 * 40 channels AWG spectral chips, with wavelength range of 880-920 nm, insertion loss of center wavelengths is better than-0.9 dB.

Analytical Review on the Modern Optimization Algorithms in Logistics

2020 ◽  
Vol 14 (1) ◽  
pp. 25-31
Author(s):  
Mohammad Zaher Akkad ◽  
Tamás Bányai
Keyword(s):  
Content Analysis ◽  
Optimization Algorithms ◽  
Hybrid Algorithms ◽  
Metaheuristic Algorithms ◽  
Complex Problems ◽  
Analytical Review ◽  
Optimum Solution ◽  
Short Time ◽  
Modern Optimization

Optimization algorithms are used to reach the optimum solution from a set of available alternatives within a short time relatively. With having complex problems in the logistics area, the optimization algorithms evolved from traditional mathematical approaches to modern ones that use heuristic and metaheuristic approaches. Within this paper, the authors present an analytical review that includes illustrative and content analysis for the used modern algorithms in the logistics area. The analysis shows accelerated progress in using the heuristic/metaheuristic algorithms for logistics applications. It also shows the strong presence of hybrid algorithms that use heuristic and metaheuristic approaches. Those hybrid algorithms are providing very efficient results.

scholarly journals A Performance Comparison of Centralized and Distributed Spectrum Management Techniques in Elastic Optical Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Tushar Mathur ◽  
Gokhan Sahin ◽  
Donald R. Ucci
Keyword(s):  
Optical Networks ◽  
Wavelength Division Multiplexing ◽  
Orthogonal Frequency Division Multiplexing ◽  
Performance Metrics ◽  
New Technology ◽  
Spectrum Management ◽  
Performance Comparison ◽  
Spectrum Efficiency ◽  
Network Simulator ◽  
Reservation Protocol

Elastic optical networks (EONs) have emerged to provide higher spectrum efficiency than traditional Dense Wavelength-Division-Multiplexing (DWDM) by utilizing enabling technologies such as flexible spectrum grid, Orthogonal Frequency Division Multiplexing (OFDM), and distance adaptive rate and modulation. The choice of the control-plane is an important consideration when deploying any new technology, especially in optical networks. This paper considers generic distributed and centralized spectrum assignment policies in conjunction with the accompanying connection set-up signaling protocols in EONs. A network simulator for Generalized Multiprotocol Label Switching (GMPLS) was developed with Forward Reservation Protocol and Backward Reservation Protocol signaling methods. These signaling techniques are used with the First Fit (FF) and Random Fit (RF) Routing and Spectrum Allocation (RSA) algorithms. The paper discusses control elements (central and distributed architectures) decisions under busy hour and normal network conditions and presents a comprehensive performance analysis of key performance metrics such as connection success rate, connection establishment time, and capacity requirement.

scholarly journals Performance Comparison of Digitized Quaternion Modulation with other Modulation Schemes

2019 ◽  
Vol 27 ◽  
pp. 01004
Author(s):  
Anam Zahra ◽  
Qasim Umar Khan
Keyword(s):  
Global Positioning System ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Performance Comparison ◽  
Superior Performance ◽  
Positioning System ◽  
Space Communication ◽  
Global Positioning ◽  
Simulation Results ◽  
Modulation Schemes

In wireless networks signal’s security from noise has been a very challenging issue, primarily because of the broadcast nature of communication. This paper focuses on digitized Quaternion Modulation (QM) which gives better performance as compared to QPSK, QAM and QFSK. We compare the performance of quaternion modulation with other modulation schemes in terms of BER using idealistic Additive White Gaussian Noise AWGN channel. This scheme can be used in applications such as Global Positioning System (GPS), satellite and space communication system to reduce errors. The simulation results show superior performance of the proposed digitized Quaternion Modulation over its counterparts. Thus one may trade off bandwidth for BER.

scholarly journals Semi-Steady-State Jaya Algorithm for Optimization

2020 ◽  
Vol 10 (15) ◽  
pp. 5388
Author(s):  
Uday K. Chakraborty
Keyword(s):  
Steady State ◽  
Evolutionary Computation ◽  
Performance Improvement ◽  
Real World ◽  
Statistical Tests ◽  
Test Suite ◽  
Jaya Algorithm ◽  
Real World Problem ◽  
Simulation Results ◽  
Population Simulation

The Jaya algorithm is arguably one of the fastest-emerging metaheuristics amongst the newest members of the evolutionary computation family. The present paper proposes a new, improved Jaya algorithm by modifying the update strategies of the best and the worst members in the population. Simulation results on a twelve-function benchmark test-suite and a real-world problem show that the proposed strategy produces results that are better and faster in the majority of cases. Statistical tests of significance are used to validate the performance improvement.

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