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2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Swarm Fractional-best Particle Swarm Optimization for Dynamic Multi-modal Optimization Simon Dennis and Andries Engelbrecht .......... 1549 Analysis of Particle Swarm Optimisation for Training Support  ...  Idoumghar .......... 465 HIDMS-PSO: A New Heterogeneous Improved Dynamic Multi-Swarm PSO Algorithm Fevzi Tugrul Varna and Phil Husbands .......... 473 PSO Trajectory Planner Using Kinematic Controllers  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Data Dissemination in VANETs using Clustering and Probabilistic Forwarding Based on Adaptive Jumping Multi-Objective Firefly Optimization

Mustafa Maad Hamdi, Lukman Audah, Sami Abduljabbar Rashid
2022 IEEE Access  
Their finding is that multi-objective firefly optimization algorithm outperforms both multi-objective particle swarm optimization and comprehensive multi-objective particle swarm optimization.  ...  Their finding is an outperformance of this variant of multi-objective firefly over non-dominated sorting genetic optimization and multi-objective particle swarm optimization.  ... 
doi:10.1109/access.2022.3147498 fatcat:fycfcvzapfffngnroojby4ogqy

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
The population evolves on a bidimensional grid and is implicitly organized in geographical clusters that present a form of structural similarity between individuals.  ...  This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm.  ...  , Mohammad Nabi Omidvar and Xiaodong Li, Reference Point Based Multi-objective Optimization Through Decomposition Tuesday, IEEE CEC, TuC 4-4, 14:40-15:40, Particle swarm optimization 6, Mengjie Zhang 330  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

A Decision-Making Framework for the Smart Charging of Electric Vehicles Considering the Priorities of the Driver

Nikolaos Milas, Dimitris Mourtzis, Emmanuel Tatakis
2020 Energies  
For the selection of the scheduling algorithm, the genetic algorithm and particle swarm optimisation have been evaluated, where the latter had better performance.  ...  Towards addressing this challenge, a framework for the smart charging of EVs is presented in this paper.  ...  Particle Swarm Optimisation (PSO) Particle Swarm Optimisation (PSO) first introduced by Eberhart and Kennedy in 1995, is a form of swarm intelligence in which the behaviour of a biological social system  ... 
doi:10.3390/en13226120 fatcat:pgn4c4if4zckxeswhs5nlnve5e

Multi-Layer Perceptron Neural Network Classifier With Binary Particle Swarm Optimization Based Feature Selection For Brain-Computer Interfaces

K. Akilandeswari, G. M. Nasira
2015 Zenodo  
It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm.  ...  Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.  ...  RELATED WORKS Smart Multi-Objective PSO using Decomposition (SDMOPSO) introduced by Moubayed [12] used a decomposition approach presented in Multi-Objective Evolutionary Algorithms based on Decomposition  ... 
doi:10.5281/zenodo.1109968 fatcat:yga7s2bmzreyveummgta3baz74

Integrated operational supply chain planning in Industry 4.0

Matheus Cardoso Pires, Renato Parreira, Enzo Morosini Frazzon
2021 The International Journal of Integrated Supply Management  
The scenario of isolated companies competing with each other has evolved to a holistic vision, where companies collaborate and work together to maintain supply chain competitiveness.  ...  This paper presents a systematic literature review on integrated supply chain planning aiming to identify research streams, opportunities and the impact of Industry 4.0.  ...  The authors proposed a novel heuristic-based discrete particle swarm optimisation (DPSO) algorithm, used with simulation approach for determining the solutions for the stochastic demand cases.  ... 
doi:10.1504/ijism.2021.113566 fatcat:3vwqxjfi2ffrfpdl3sjqiisxmi

Intelligent, smart and scalable cyber-physical systems

V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy, Longzhi Yang, V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy, Longzhi Yang
2019 Journal of Intelligent & Fuzzy Systems  
efficiently manage real-world processes and offers a broad range of novel applications and services.  ...  As CPSs hold strong interactions between the cyber and physical components, it plays a significant role in the development of next-generation efficient-smart systems in various real-time applications.  ...  Compared with traditional multi-scale and multi-direction decomposition based algorithms, a more efficient MSMD based algorithm is proposed.  ... 
doi:10.3233/jifs-179108 fatcat:4hghoxr4prccxjpfg5juwzoie4

Coordinated optimisation of PEV charging with the support of reactive discharging and phase switching in unbalanced active distribution networks

Yang Fu, Xianghao Meng, Xiangjing Su, Nasim Jabalameli, Zhaoyang Dong
2020 IET Generation, Transmission & Distribution  
The optimal power flow problem defined above is solved by a combined solver of discrete particle swarm optimisation and direct load flow.  ...  This study proposes a novel coordination strategy of PEV charging in unbalanced distribution networks, with the support of reactive discharging and phase switching.  ...  [9] presented a multi-objective optimisation strategy for coordinated PEV charging, to minimise the load peak-valley difference and the user cost.  ... 
doi:10.1049/iet-gtd.2020.0117 fatcat:t5q47ktgv5cqzo7lsvfo5v7joi

Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors

A. A. Masrur Ahmed, Ekta Sharma, S. Janifer Jabin Jui, Ravinesh C. Deo, Thong Nguyen-Huy, Mumtaz Ali
2022 Remote Sensing  
swarm optimisation) methods that are implemented using a set of carefully screened satellite variables and a feature decomposition or CEEMDAN approach.  ...  ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the grey wolf optimisation (GWO).  ...  The particle swarm optimiser algorithm is a population-based stochastic optimisation inspired by social and psychological considerations [57] .  ... 
doi:10.3390/rs14051136 fatcat:s6rtgqaotzh6ppt5qznvgjmi7m

Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

Lijo Jacob Varghese, K. Dhayalini, Suma Sira Jacob, Ihsan Ali, Abdelzahir Abdelmaboud, Taiseer Abdalla Elfadil Eisa
2022 Computers Materials & Continua  
In order to overcome fulfill this research gap, the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm (MOGOA) with Deep Extreme Learning Machine (DELM)-based short-term  ...  To inspect the effectual outcome of the proposed MOGOA-DELM model, a series of simulations was performed using UK Smart Meter dataset. In the experimentation procedure, the proposed  ...  [11] developed a new model through hybridization of ELM switching delayed Particle Swarm Optimisation (PSO) technique to forecast the short-term load.  ... 
doi:10.32604/cmc.2022.019435 fatcat:u5hei5tz3rh33l64l6jkn4ytti

Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review

Ioannis Antonopoulos, Valentin Robu, Benoit Couraud, Desen Kirli, Sonam Norbu, Aristides Kiprakis, David Flynn, Sergio Elizondo-Gonzalez, Steve Wattam
2020 Renewable & Sustainable Energy Reviews  
Swarm Intelligence algorithms most commonly found in the literature are Particle Swarm Optimisation (PSO) algorithm [151] , and Ant Colony Optimisation (ACO) [152] .  ...  The scheduling can actually be considered as a constrained multi-objective optimisation problem. Regarding load scheduling, Pedrasa et al.  ...  [145] 2017 NSGA-II Multi-objective scheduling for RTP. 85 Herath and Venayagamoorthy [158] 2017 Multi-objective PSO Load scheduling for DR. 86 Kazemi et al.  ... 
doi:10.1016/j.rser.2020.109899 fatcat:wgpj4awq35dfzdq7ugumtrvo7q

Electric Vehicles in a smart grid: A comprehensive survey on optimal location of charging station

Mohd Bilal, M. Rizwan
2020 IET Smart Grid  
Various approaches, objective functions, constraints and range of optimisation techniques are addressed by researchers for optimal placement of CS.  ...  CS placement is a matter of great concern for large scale penetration of EVs.  ...  Evolutionary algorithm Particle swarm optimisation (PSO): PSO deals with the social behaviour of the number of particles in a swarm, and each particle is presented as a solution to the problem.  ... 
doi:10.1049/iet-stg.2019.0220 fatcat:deszlot24behfebavwdk2wv5sq

Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

Pavlos S. Georgilakis, Charalampos Arsoniadis, Christos A. Apostolopoulos, Vassilis C. Nikolaidis
2021 IET Smart Grid  
The emergence of smart distribution system (SDS) with advanced distribution automation (DA) and communication infrastructure offers a great opportunity to improve reliability, through the automation of  ...  To obtain the optimal allocation of PCD (OAPCD), an optimisation problem has to be formulated and solved. Several models and methods have been suggested for the OAPCD in SDSs.  ...  Another example is ABC, which is a nature-inspired optimisation algorithm that solves complex optimisation problems by simulating the food search of bee swarm.  ... 
doi:10.1049/stg2.12017 fatcat:tt5lzwvr5jhw5d7rtbr5x3mfce

Welcome message from the General Chairs

Giovanni Giambene, Boon Sain Yeo
2009 2009 International Workshop on Satellite and Space Communications  
This year we received a total of 153 high-quality papers from more than 20 countries. Many papers demonstrated notable systems with good analytical and/or empirical analyses.  ...  Optimisation, Evolutionary Multi-objective Optimisation Algorithms, Evolutionary Algorithm, etc.  ...  Keywords: Multi-objective evolutionary algorithm, Hybrid, Decomposition. 16:20 hrs A Uniform Evolutionary Algorithm based on Decomposition and Contraction for Many-objective Optimization Problems Cai  ... 
doi:10.1109/iwssc.2009.5286448 fatcat:wcu4uzasizhzjmdkzyekynnqwi

Many-Objective Optimization of a Hybrid Car Controller [chapter]

Tobias Rodemann, Kaname Narukawa, Michael Fischer, Mohammed Awada
2015 Lecture Notes in Computer Science  
In this paper, we present an EMS for buildings that uses a novel approach towards optimization of energy flows.  ...  In the multi-noisy-objective optimization problem of the SAW filter, the worst-case performance of a solution is considered based on the upper bounds of respective noisy-objective functions predicted statistically  ...  In this work we present a Multi Objective Genetic Algorithm (MOGA) using the diversity-as-objective (DAO) variant of multi-objectivisation, to optimise secondary structure similarity and sequence diversity  ... 
doi:10.1007/978-3-319-16549-3_48 fatcat:yvlv6xnggnf3jn7vdnnwih6chy
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