Search results for "Ant colony optimization"

showing 10 items of 33 documents

A Probabilistic Approach to the Count-To-Infinity Problem in Distance-Vector Routing Algorithms

2013

Count-to-infinity problem is characteristic for routing algorithms based on the distributed implementation of the classical Bellman-Ford algorithm. In this paper a probabilistic solution to this problem is proposed. It is argued that by the use of a Bloom Filter added to the routing message the routing loops will with high probability not form. An experimental analysis of this solution for use in Wireless Sensor Networks in practice is also included.

Distance-vector routing protocolLink-state routing protocolComputer scienceAnt colony optimization algorithmsComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSMultipath routingComputer Science::Networking and Internet ArchitectureProbabilistic logicPath vector protocolProbabilistic analysis of algorithmsRouting (electronic design automation)Algorithm
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Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm

2007

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the i…

EngineeringMathematical optimizationCogeneration distributed generation gas microturbines power distribution economics power distribution planningbusiness.industryEnergy managementAnt colony optimization algorithmsEnergy Engineering and Power TechnologyAnt colonyTechnology managementSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSearch algorithmDistributed generationEnergy marketTrading strategyElectrical and Electronic Engineeringbusiness
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Fuzzy predictive controller design using ant colony optimization algorithm

2014

In this paper, an approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the Ant Colony Optimization (ACO) is studied. On-line adaptive fuzzy identification is used to identify the system parameters. These parameters are used to calculate the objective function based on predictive approach and structure of RST control. The optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to calculate a sequence of future RST control actions. The obtained simulation results show that proposed approach provides better results compared with Proportional Integral-Ant Colony Optimization (PI-ACO) controller and adaptive fuzzy model pr…

EngineeringMeta-optimizationOptimization problemLinear programmingbusiness.industryAnt colony optimization algorithmsComputer Science Applications1707 Computer Vision and Pattern RecognitionComputingMethodologies_ARTIFICIALINTELLIGENCEFuzzy logicModel predictive controlControl theoryControl and Systems EngineeringModeling and SimulationModeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Control and Systems Engineering; Electrical and Electronic EngineeringElectrical and Electronic EngineeringbusinessAlgorithmMetaheuristic
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Backcalculation of airport pavement moduli and thickness using the Lévy Ant Colony Optimization Algorithm

2016

Interpretation of NDTdata is crucial in any Airport Pavement Management System (APMS), in order to implement strategies to maintain airport pavementssince they allow to estimate their remaining life and related maintenance needs and activities. In this paper, the AntColony Optimization algorithmwasused for backcalculation of pavement moduli from surface deflection data. The algorithm’s performances are illustrated and improvement in prediction quality is demonstrated both in terms of goodness of fitness and computational effort. Moreover, it is proved that the proposed algorithm is also able to predict layer thicknesses, taking into account their variation too.

Engineeringmoduli backcalculation0211 other engineering and technologies020101 civil engineering02 engineering and technologyheuristic algorithm.0201 civil engineeringModuliDeflection (engineering)Nondestructive testing021105 building & constructionSettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials ScienceFWD dataCivil and Structural Engineeringbusiness.industryAnt colony optimization algorithmsPavement managementBuilding and ConstructionAbstract interpretationRemaining lifeNon Destructive TestingbusinessSettore ICAR/08 - Scienza Delle CostruzioniAlgorithmairport pavement
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An Application of Ant Colony Optimization to Decision Making on Affective Virtual Entities

2007

Learning is a never ending activity for humans; it takes place everywhere and even when we do not realize. However, current learning environments make students deal with lectures, mostly associated with low control of the situation and implicit motivation. In contrast, previous researches have shown that sports, games or hobbies are activities that make people reach optimal experiences where self-motivation, control of the situation, high level of concentration and enjoyment are present. Some current efforts to design next generation of learning environments make use of ubiquitous systems to encourage students to perform learning activities everywhere and at anytime. However, those approach…

EntertainmentUbiquitous systemsUbiquitous computingMultimediaComputer scienceAnt colony optimization algorithmsControl (management)Augmented realityUbiquitous learning environmentComputer aided instructioncomputer.software_genrecomputerNinth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2007)
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Strategies for accelerating ant colony optimization algorithms on graphical processing units

2007

Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.

Extremal optimizationMathematical optimizationTheoretical computer scienceOptimization problemComputer scienceComputationAnt colony optimization algorithmsArtificial lifeMetaheuristicParallel metaheuristic2007 IEEE Congress on Evolutionary Computation
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An ant colony optimization-based fuzzy predictive control approach for nonlinear processes

2015

In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with p…

Information Systems and ManagementMeta-optimizationOptimization problemComputer scienceAnt colony optimization algorithmsComputer Science::Neural and Evolutionary ComputationProcess (computing)Computer Science ApplicationsTheoretical Computer ScienceNonlinear systemModel predictive controlArtificial IntelligenceControl and Systems EngineeringControl theoryMetaheuristicSoftwareInformation Sciences
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Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem

2015

Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…

Mathematical optimizationComputer scienceAnt colony optimization algorithmsMathematicsofComputing_NUMERICALANALYSISMemetic algorithmAnt colony2-optComputingMethodologies_ARTIFICIALINTELLIGENCESwarm intelligenceMetaheuristicTravelling salesman problemParallel metaheuristic
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α-stable distributions for better performance of ACO in detecting damage on not well spaced frequency systems

2014

Abstract In this paper, the Ant Colony Optimization (ACO) algorithm is modified through α -stable Levy variables and applied to the identification of incipient damage in structural components. The main feature of the proposed optimization is an improved ability, which derives from the heavy tails of the stable random variable, to escape from local minima. This aspect is relevant since the objective function used for damage detection may have many local minima which render very challenging the search of the global minimum corresponding to the damage parameter. As the optimization is performed on the structural response and does not require the extraction of modal components, the method is pa…

Mathematical optimizationDamage detectionComputer scienceMechanical EngineeringAnt colony optimization algorithmsAnt Colony Optimization Damage identification Lévy α-stable distributions Not-well spaced frequency systemAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsCondensed Matter PhysicsMaxima and minimaModalNuclear Energy and EngineeringFeature (computer vision)Biological systemRandom variableCivil and Structural Engineering
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On Randomness and Structure in Euclidean TSP Instances: A Study With Heuristic Methods

2021

Prediction of the quality of the result provided by a specific solving method is an important factor when choosing how to solve a given problem. The more accurate the prediction, the more appropriate the decision on what to choose when several solving applications are available. In this article, we study the impact of the structure of a Traveling Salesman Problem instance on the quality of the solution when using two representative heuristics: the population-based Ant Colony Optimization (ACO) and the local search Lin-Kernighan (LK) algorithm. The quality of the result for a solving method is measured by the computation accuracy, which is expressed using the percent error between its soluti…

Mathematical optimizationGeneral Computer ScienceComputer scienceHeuristic (computer science)Population0211 other engineering and technologies02 engineering and technologyTravelling salesman problemAnt colony optimizationApproximation error0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceLocal search (optimization)Electrical and Electronic EngineeringeducationRandomnessLin-Kernighan methodeducation.field_of_study021103 operations researchEuclidean normHeuristicbusiness.industryAnt colony optimization algorithmstraveling salesman problemGeneral EngineeringApproximation algorithm020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringHeuristicsbusinesslcsh:TK1-9971IEEE Access
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