Search results for "Continuous optimization"

showing 10 items of 10 documents

Combinatorial Optimization for Artificial Intelligence Enabled Mobile Network Automation

2021

This chapter discusses combinatorial optimization techniques for enabling intelligent automation in mobile networks. A number of discrete optimization problems pertinent to mobile network automation can be solved effectively using artificial intelligence based combinatorial optimization approaches such as heuristics and metaheuristics. Relevant use-cases include both initial parameter assignment during network roll-out, and continuous optimization of configuration management parameters during network operation and maintenance. We discuss mobile network automation use-cases and motivation for using different heuristics and metaheuristics in designing network optimization algorithms. To this …

Continuous optimizationComputer sciencebusiness.industryCellular networkCombinatorial optimizationArtificial intelligenceHeuristicsbusinessAssignment problemMetaheuristic5GNetwork model
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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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Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization

2008

The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…

Continuous optimizationMathematical optimizationEstimation theoryComputer scienceCumulative distribution functionAnt colony optimization algorithmsAnt colonyAlgorithmSearch treeEvolutionary computationWeibull distribution2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)
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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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Black box scatter search for general classes of binary optimization problems

2010

The purpose of this paper is to apply the scatter search methodology to general classes of binary problems. We focus on optimization problems for which the solutions are represented as binary vectors and that may or may not include constraints. Binary problems arise in a variety of settings, including engineering design and statistical mechanics (e.g., the spin glass problem). A distinction is made between two sets of general constraint types that are handled directly by the solver and other constraints that are addressed via penalty functions. In both cases, however, the heuristic treats the objective function evaluation as a black box. We perform computational experiments with four well-k…

Continuous optimizationMathematical optimizationOptimization problemGeneral Computer ScienceL-reductionManagement Science and Operations ResearchMulti-objective optimizationEngineering optimizationVector optimizationModeling and SimulationPenalty methodAlgorithmMetaheuristicMathematicsComputers & Operations Research
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SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization

2007

We describe the development and testing of a metaheuristic procedure, based on the scatter-search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of scatter search to multiobjective optimization problems has not been fully explored in the literature. We test the proposed procedure on a suite of problems that have been used extensively in multiobjective optimization. Additional tests are performed on instances that are an extension of those consid…

Continuous optimizationNonlinear systemMultiobjective optimization problemMathematical optimizationComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSISGeneral EngineeringEfficient frontierMulti-objective optimizationMetaheuristicGlobal optimizationTabu searchMathematicsINFORMS Journal on Computing
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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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Disturbed Exploitation compact Differential Evolution for Limited Memory Optimization Problems

2011

This paper proposes a novel and unconventional Memetic Computing approach for solving continuous optimization problems characterized by memory limitations. The proposed algorithm, unlike employing an explorative evolutionary framework and a set of local search algorithms, employs multiple exploitative search within the main framework and performs a multiple step global search by means of a randomized perturbation of the virtual population corresponding to a periodical randomization of the search for the exploitative operators. The proposed Memetic Computing approach is based on a populationless (compact) evolutionary framework which, instead of processing a population of solutions, handles …

Continuous optimizationta113education.field_of_studyMathematical optimizationInformation Systems and ManagementOptimization problemdifferential evolutionCrossoverPopulationEvolutionary algorithmComputer Science ApplicationsTheoretical Computer ScienceArtificial IntelligenceControl and Systems Engineeringmemetic computingDifferential evolutionMemetic algorithmevolutionary algorithmseducationcompact algorithmsSoftwarePremature convergenceMathematicsInformation Sciences
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A multi-local optimization algorithm

1998

The development of efficient algorithms that provide all the local minima of a function is crucial to solve certain subproblems in many optimization methods. A “multi-local” optimization procedure using inexact line searches is presented, and numerical experiments are also reported. An application of the method to a semi-infinite programming procedure is included.

Statistics and ProbabilityContinuous optimizationMathematical optimizationInformation Systems and ManagementMeta-optimizationManagement Science and Operations ResearchSemi-infinite programmingMaxima and minimaVector optimizationModeling and SimulationDiscrete Mathematics and CombinatoricsRandom optimizationMulti-swarm optimizationAlgorithmMetaheuristicMathematicsTop
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Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows

2016

International audience; In our study, we develop a method that merges two information sources within ants colony optimization heuristic. Namely artificial ants which occurs for short term optimization and transporter's vehicles that occurs in long term and continuous optimization toward solving the real-world vehicle routing problem. This study is supported by a transporter (Upsilon) of the region of l'Yonne in France and a transport and logistics software development company (Tedies). Our method suits for transporters that use human planners to make decisions about their tours and intending to move to computer planners without drastically upsetting the drivers habits. Hence, the pledge of …

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Operations researchComputer scienceHeuristic (computer science)0211 other engineering and technologies02 engineering and technology[INFO] Computer Science [cs]Pledge[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Software[ SPI.NRJ ] Engineering Sciences [physics]/Electric powerVehicle routing problem0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]SimulationContinuous optimization021103 operations researchbusiness.industryAnt colony optimization algorithms[SPI.NRJ]Engineering Sciences [physics]/Electric powerSoftware development[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsTerm (time)020201 artificial intelligence & image processingbusiness[SPI.NRJ] Engineering Sciences [physics]/Electric power
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