Search results for "Swarm"

showing 10 items of 100 documents

Categories, Quantum Computing, and Swarm Robotics: A Case Study

2022

The swarms of robots are examples of artificial collective intelligence, with simple individual autonomous behavior and emerging swarm effect to accomplish even complex tasks. Modeling approaches for robotic swarm development is one of the main challenges in this field of research. Here, we present a robot-instantiated theoretical framework and a quantitative worked-out example. Aiming to build up a general model, we first sketch a diagrammatic classification of swarms relating ideal swarms to existing implementations, inspired by category theory. Then, we propose a matrix representation to relate local and global behaviors in a swarm, with diagonal sub-matrices describing individual featur…

Computer Science::RoboticsSwarm roboticsswarm robotics; quantum computing; 4-qubit system; matrix representation; colimitGeneral MathematicsColimitQA1-939Computer Science (miscellaneous)4-qubit systemQuantum computingMatrix representationEngineering (miscellaneous)MathematicsMathematics
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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…

Computer sciencepäätöksentekomultiple criteria decision makingContext (language use)02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesMulti-objective optimizationoptimointi0202 electrical engineering electronic engineering information engineeringmultiobjective optimization0101 mathematicsToma de decisionespreference articulationparticle swarm optimizationbusiness.industryParticle swarm optimizationDecision makermonitavoiteoptimointiPreferenceMulti-objective optimization010101 applied mathematicsBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer
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An Adaptive Metamodel-Based Optimization Approach for Vehicle Suspension System Design

2014

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/965157 The performance index of a suspension system is a function of the maximum and minimum values over the parameter interval. Thus metamodel-based techniques can be used for designing suspension system hardpoints locations. In this study, an adaptive metamodel-based optimization approach is used to find the proper locations of the hardpoints, with the objectives considering the kinematic performance of the suspension. The adaptive optimization method helps to find the optimum locations of the hardpoints efficiently as it may be unachie…

Continuous optimizationMathematical optimizationEngineeringArticle SubjectAdaptive optimizationbusiness.industryGeneral MathematicsProbabilistic-based design optimizationlcsh:MathematicsVDP::Technology: 500::Mechanical engineering: 570General EngineeringInterval (mathematics)Kinematicslcsh:QA1-939Multi-objective optimizationEngineering (all)lcsh:TA1-2040Mathematics (all)Multi-swarm optimizationbusinessSuspension (vehicle)lcsh:Engineering (General). Civil engineering (General)Mathematics (all); Engineering (all)Mathematical Problems in Engineering
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An evolutionary method for complex-process optimization

2010

10 páginas, 7 figuras, 7 tablas

Continuous optimizationMathematical optimizationOptimization problemGeneral Computer ScienceEvolutionary algorithmMetaheuristicsManagement Science and Operations ResearchEvolutionary algorithmsMulti-objective optimizationComplex-process optimizationContinuous optimizationModeling and SimulationGenetic algorithmDerivative-free optimizationGlobal optimizationMulti-swarm optimizationMetaheuristicMathematicsComputers & Operations Research
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Memetic Algorithms in Continuous Optimization

2012

Intuitively, a set is considered to be discrete if it is composed of isolated elements, whereas it is considered to be continuous if it is composed of infinite and contiguous elements and does not contain “holes”.

Continuous optimizationSet (abstract data type)Mathematical optimizationComputer sciencebusiness.industryDifferential evolutionMemetic algorithmParticle swarm optimizationLocal search (optimization)businessMetaheuristic
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Comparison of different cooperation strategies in the prey-predator problem

2006

The paper describes two cooperating strategies among several homogeneous agents to reach a given target. In our case we used the prey-predators paradigm in which a set of agents (predators) have the purpose to reach a target (prey). The problem is addressed as an optimization problem that has been faced with two different algorithms (a genetic algorithm and a particle swam optimization algorithm). The two approaches are evaluated by using a simulator for each strategy and the results show that the strategies are very different in terms of prey-predator successes. Genetic algorithm can be used by the prey to solve at the best the problem to reach the lair, otherwise the Particle Swarm Optimi…

Cooperation strategieParticle Swam optimizationPrey-predatorSettore INF/01 - Informaticaoptimiz ation problemHomogeneous agentInternational (CO)Machine perceptionParticle swarm optimization method2006 International Workshop on Computer Architecture for Machine Perception and Sensing
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Konteineru tehnoloģijas izmantošana programmatūras izstrādē

2019

Pēdējo gadu laikā, kopš Docker parādīšanās, strauji ir pieaugusi konteineru tehnoloģijas izmantošana programmatūras izstrādē, tādēļ bakalaura darba mērķis ir izpētīt šo tehnoloģiju, apskatīt tās pamatus, uzbūvi, realizācijas veidus un kā to var pielietot programmatūras izstrādē, kā arī praktiski izmēģināt kādu no apskatītajām tehnoloģijas implementācijām.

DockerDatorzinātnekonteineriKubernetesDocker Swarm
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Optimal power flow for technically feasible energy management systems in islanded microgrids

2016

This paper presents a combined optimal energy and power flow management for islanded microgrids. The highest control level in this case will provide a feasible and optimized operating point around the economic optimum. In order to account for both unbalanced and balanced loads, the optimal power flow is carried out using a Glow-worm Swarm Optimizer. The control level is organized into two different sub-levels, the highest of which accounts for minimum cost operation and the lowest one solving the optimal power flow and devising the set points of inverter interfaced generation units and rotating machines with a minimum power loss. A test has been carried out for 6 bus islanded microgrids to …

Droop controldroop controlEngineeringMicrogridEnergy management020209 energyGlow-worm swarm optimizationglow-worm swarm optimizationEnergy Engineering and Power Technology02 engineering and technologySet (abstract data type)Control theory0202 electrical engineering electronic engineering information engineeringoptimal power flowElectrical and Electronic EngineeringOperating pointRenewable Energy Sustainability and the Environmentbusiness.industrySwarm behaviourSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiamicrogridInverterMicrogridbusinessOptimal power flowEnergy (signal processing)Power control2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)
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KIC 8462852: Will the Trojans return in 2021?

2017

KIC 8462852 stood out among more than 100,000 stars in the Kepler catalogue because of the strange features of its light curve: a wide, asymmetric dimming taking up to 15 per cent of the light at D793 and a period of multiple, narrow dimmings happening approximately 700 days later. Several models have been proposed to account for this abnormal behaviour, most of which require either unlikely causes or a finely-tuned timing. We aim at offering a relatively natural solution, invoking only phenomena that have been previously observed, although perhaps in larger or more massive versions. We model the system using a large, ringed body whose transit produces the first dimming and a swarm of Troja…

Earth and Planetary Astrophysics (astro-ph.EP)Physics010308 nuclear & particles physicsFOS: Physical sciencesSwarm behaviourAstronomyAstronomy and AstrophysicsAstrophysicsLight curveOrbital period01 natural sciencesKeplerStarsOrbitSpace and Planetary ScienceTrojan0103 physical sciencesAstrophysics::Earth and Planetary AstrophysicsTransit (astronomy)010303 astronomy & astrophysicsAstrophysics - Earth and Planetary AstrophysicsMonthly Notices of the Royal Astronomical Society: Letters
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Passive congregation based particle swam optimization (pso) with self-organizing hierarchical approach for non-convex economic dispatch

2017

This paper proposes a passive congregation based PSO with self-organizing hierarchical algorithm approach for solving the economic dispatch problem of power system, where some of the units have prohibited operating zones. This Algorithm is known to perform better than conventional gradient based optimization methods for non-convex optimization problems. Conventional PSO algorithm is a population based heuristic search, employing problem of premature convergence. In this work, an innovative approach based on the concept of passive congregation based PSO with self-organizing hierarchical approach is employed to overcome the problem of premature convergence in classical PSO method.

Electric power systemMathematical optimizationOptimization problemConvergence (routing)MathematicsofComputing_NUMERICALANALYSISRegular polygonEconomic dispatchParticle swarm optimizationPremature convergenceHierarchical algorithm2017 2nd International Conference on Power and Renewable Energy (ICPRE)
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