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Multiswarms, exclusion, and anti-convergence in dynamic environments
2006
IEEE Transactions on Evolutionary Computation
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In addition, each swarm maintains diversity either by using charged or quantum particles. ...
Index Terms-Dynamic environments, genetic algorithms, optimization methods, particle swarm optimization (PSO). ...
This approach has been inspired by multipopulation EA approaches like the self-organizing scouts developed by Branke [13] , which have shown to give excellent results on the tested problems. ...
doi:10.1109/tevc.2005.857074
fatcat:n7j2k5nwqvcxhebsyg2uyicr54
A quarter century of particle swarm optimization
2018
Complex & Intelligent Systems
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Over the past quarter century, the particle swarm optimization algorithm has attracted many researchers' attention. ...
With the analysis of different evolution and learning strategies, particle swarm optimization algorithm could be utilized on solving more real-world application problems effectively, and the strength and ...
, -Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC) [66] , -Adaptive particle swarm optimization (APSO) [96] . 2. ...
doi:10.1007/s40747-018-0071-2
fatcat:rajjkozus5govjy7kgnwix5edm
Multimodal optimization for time-cost trade-off in construction projects using a novel hybrid method based on FA and PSO
Optimización multimodal para la compensación de tiempo-costo, en proyectos de construcción, usando un nuevo método híbrido, basado en FA y PSO
2018
Revista de la construcción
Optimización multimodal para la compensación de tiempo-costo, en proyectos de construcción, usando un nuevo método híbrido, basado en FA y PSO
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This paper presents a new algorithm called F-PSO which consists of hybridizing Firefly Algorithm (FA) with Particle Swarm Optimization (PSO). ...
In this method, the problem is modelled with various execution modes to select the optimal one for each activity. ...
Particle swarm optimization (PSO) is a type of swarm based algorithm inspired by nature. ...
doi:10.7764/rdlc.17.2.304
fatcat:mbeyzgqdcnbdxlrhmr523b3dxi
Particle Swarm Optimization Methods, Taxonomy and Applications
2009
Journal of clean energy technologies
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The Particle Swarm Optimization (PSO) algorithm, as one of the latest algorithms inspired from the nature, was introduced in the mid 1990s and since then, it has been utilized as an optimization tool in ...
Objective -Considering that optimization problems are divided to single-objective and multi-objective problems from the view of objective numbers, the multi-objective and single-objective approaches have ...
In the multi-objective approach, it is tried to optimize several objectives using one swarm and according to the priority of the objectives. ...
doi:10.7763/ijcte.2009.v1.80
fatcat:nwuursqzyzefxl5dadvhdxlbda
Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review
2021
IEEE Access
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Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization ...
INTERIOR POINT (IP) ALGORITHMS APPLIED ON STHTS PROBLEM According to [2], reference [52], implemented the primal-dual IP algorithm to solve the CSTHTS problem on Brazilian 25998 VOLUME 9, 2021 ...
Reference [99] has solved the CSTHTS problem using a variant of canonical PSO, known as self-organizing hierarchical particle swarm optimization in which the acceleration coefficients of the particles ...
doi:10.1109/access.2021.3055292
fatcat:xnb7xfhvgbht3diqqnht633b6u
A survey of swarm intelligence for dynamic optimization: Algorithms and applications
2017
Swarm and Evolutionary Computation
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Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish swarm optimization ...
This paper presents a broad review on SI dynamic optimization (SIDO) focused on several classes of problems, such as discrete, continuous, constrained, multi-objective and classification problems, and ...
Inspired from the atom field, Blackwell et al. [97] introduced a multi-charged PSO (mCPSO) and a multi-quantum swarm optimization (mQSO). ...
doi:10.1016/j.swevo.2016.12.005
fatcat:ro3x4hds5vc7ri42szwdhby3bq
Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives
2018
Machine Learning and Knowledge Extraction
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2018 pre-print arXiv:1804.05319v1 fatcat:wnvmathlqzcf7kp2uvfxtrstaeOther Versions
The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. ...
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional ...
[199] modeled complex network clustering as a multi-objective optimization problem and applied a quantum inspired discrete particle swarm optimization algorithm with non-dominated sorting for individual ...
doi:10.3390/make1010010
fatcat:ue65xvqyk5hovlzo6gzok524pm
Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs
2012
2012 IEEE Congress on Evolutionary Computation
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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. ...
The population evolves on a bidimensional grid and is implicitly organized in geographical clusters that present a form of structural similarity between individuals. ...
Optimization 537, Asad Mohammadi, 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 ...
doi:10.1109/cec.2012.6256590
dblp:conf/cec/RotaruB12
fatcat:4ly3nrktw5habc6lf5err7d5py
THE DAWN OF METAHEURISTIC ALGORITHMS
2018
International Journal of Software Engineering and Computer Systems
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since the optimization algorithms are the engine room of successful optimization enterprise. ...
At the heart of efficiency and effectiveness of optimization of engineering, business and industrial processes is metaheuristics, hence the need for proper explanations of the basics of optimization algorithms ...
Furthermore, in a situation where = 1, then it is an instance of single objective function; in a situation where ≥ 2, that is a multi-objective problem. ...
doi:10.15282/ijsecs.4.2.2018.4.0048
fatcat:np2dahmksjbxhegdr6wckr7p7q
Metaheuristics Method for Computation Offloading In Mobile Edge Computing: Survey
2023
Journal of Advanced Research in Applied Sciences and Engineering Technology
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The proposed taxonomy is classified into three main fields: genetic algorithm (GA)-based mechanisms, Partical Swarm Optimization(PSO)-based mechanisms, and Hybrid GA with PSO -based mechanisms. ...
essential challenging problems in the MEC environment. ...
The particle swarm optimization (PSO) is then an algorithm based on self-organizing systems 'collective and decentralized behaviour. ...
doi:10.37934/araset.36.1.4373
fatcat:rqglqjq4d5auvnp7fbym4n5qmu
A Review of Quantum-Inspired Metaheuristic Algorithms for Automatic Clustering
2023
Mathematics
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The fundamental concepts of the quantum computing paradigm are also presented to highlight the utility of quantum-inspired algorithms. ...
Several automatic clustering algorithms assisted by quantum-inspired metaheuristics have been developed in recent years. ...
based on the principle of the quantum computing mechanism to handle multimodal multi-objective optimisation problems (MMO_SO_QPSO) [277] , a new quantumbased multi-objective simulated annealing technique ...
doi:10.3390/math11092018
fatcat:5d6v2tt2bfg57kdgwlh7f3k34u
A Level-Based Learning Swarm Optimizer for Large-Scale Optimization
2018
IEEE Transactions on Evolutionary Computation
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Feng, “A global search strategy of quantum-
[16] Q. Qin, S. Cheng, Q. Zhang, L. Li, and Y. Shi, “Particle swarm optimiza- behaved particle swarm optimization,” in Proc. IEEE Conf. Cybern. ...
Suganthan, “Dynamic multi-swarm particle swarm
[12] M. A. M. de Oca, T. Stutzle, K. V. den Enden, and M. Dorigo, optimizer with local search,” in Proc. IEEE Congr. Evol. ...
doi:10.1109/tevc.2017.2743016
fatcat:za37cjkibrgnfkocnafmyb5tuu
Many-Objective Quantum-Inspired Particle Swarm Optimization Algorithm for Placement of Virtual Machines in Smart Computing Cloud
2021
Entropy
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Numerical experiments have confirmed that multi-objective quantum-inspired particle swarm optimization algorithm provides better solutions than the other metaheuristics. ...
We consider the multi-criteria optimization problem of deep learning-based models embedded into virtual machines. ...
A self-organizing quantum-inspired particle swarm optimization algorithm (MMO_SO_QPSO) is another version of PSO for solving multimodal multi-objective optimization problems (MMOPs) [20] . ...
doi:10.3390/e24010058
pmid:35052084
pmcid:PMC8775184
fatcat:zc3vyht7traxtnx76ksw3wv6ei
A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT
2021
IEEE Access
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optimization while solving complex multimodal problems. ...
QUANTUM PARTICLE SWARM OPTIMIZATION Particle Swarm Optimization (PSO) proposed by Kennedy et al. ...
doi:10.1109/access.2021.3115026
fatcat:k5hgzparfvegjayi53sodpqkqu
Overview on Binary Optimisation using Swarm-inspired Algorithms
2021
IEEE Access
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Among multiple nature inspirations and versions, the dilemma of choosing proper swarm-based algorithms for each type of problem prevents their recurrent application. ...
Swarm Intelligence is applied to optimisation problems due to its robustness, scalability, generality, and flexibility. ...
Zouache et al. introduced the Quantum-Inspired Firefly Algorithm with Particle Swarm Optimization (QIFAPSO) to solve the same task. ...
doi:10.1109/access.2021.3124710
fatcat:v7heosioojg3pcwpswm3yvmrmy
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