evolutionary algorithms (EAs)
Solving unrestricted parallel machine scheduling problems via evolutionary algorithms
... The evolutionary algorithms to be developed belong to the multirecombined ...improve EAs performance by reinforcing and balancing exploration and exploitation in the search ...
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Enhancing evolutionary algorithms through recombination and parallelism
... of algorithms: Evolutionary Algorithms ...These algorithms process populations of solutions as opposed to most traditional approaches which improve a single ...these algorithms share ...
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Enhancing evolutionary algorithms through recombination and parallelism
... of algorithms: Evolutionary Algorithms ...These algorithms process populations of solutions as opposed to most traditional approaches which improve a single ...these algorithms share ...
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Optimization of coefficients of lists of polynomials by evolutionary algorithms
... the gcd (greatest common divisor) of all coefficients of the polynomials, the resulting integers are minimized in absolute value. Evolution strategies, a special class of heuristic, evolutionary algorithms, ...
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Improving evolutionary algorithms performance by extending incest prevention
... Provision of population diversity is one of the main goals to avoid premature convergence in Evolutionary Algorithms (EAs). In this way the risk of being trapped in local optima is minimised. ...
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Evolutionary algorithms to face computer systems management problems
... The inclusion of intelligence into computer systems was a long overdue project. When the results of AI research became widely applicable, Blair et al. [1] and Nicol et al. [10] proposed a holistic approach for operating ...
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Parallel evolutionary algorithms in telecommunications: two case studies
... parallel evolutionary algorithms (EAs) are developed and evaluated on two hard optimisation problems arising in the field of Telecommunications: designing error correcting codes, and finding optimal ...
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Sensor resource management with evolutionary algorithms applied to indoor positioning
... multi-objective evolutionary algorithms that optimize several metrics of the covariance of the estimation, such as average mean squared error in the area, isotropy of the solution, or the maximum deviation ...
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Sensor resource management with evolutionary algorithms applied to indoor positioning
... multi-objective evolutionary algorithms that optimize several metrics of the covariance of the estimation, such as average mean squared error in the area, isotropy of the solution, or the maximum deviation ...
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An efficient constraint handling methodology for multi-objective evolutionary algorithms
... Evolutionary algorithms (EA) have been widely used in the solution of optimization problems. These techniques, compared with the traditional nonlinear programming methods, handle a smaller amount of ...
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A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
... adaptive evolutionary algorithm to solve the NK landscape problem, which dynamically selects the recombination operator from an operator pool during the evolution; this removes the need of specifying a single ...
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Migrants Selection and Replacement in Distributed Evolutionary Algorithms for Dynamic Optimization
... of algorithms is tested using four dynamic functions (Onemax, Royal-Road, P-Peaks, and MMDP) built with the XOR-DOP benchmark genera- tor [10], thus addressing different difficulties: epistasis, multimodality, and ...
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TítuloPredicting vertical urban growth using genetic evolutionary algorithms in Tokyo’s minato ward
... The evolutionary process incorporated economic and demographic data to predict the number of new high-rise developments ...the evolutionary computation process in predicting of the number of future ...
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Optimization of distribution networks using evolutionary algorithms
... Another well-known method to optimize DNs is the Optimal Placement and Sizing of dis- tributed generation (DG) (e.g. see [10, 28]) for a given network topology. The implementa- tion of new generators, in radial ...
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Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms
... An architecture, called Red Swarm, with the aim of reducing travel times is presented in [11]. There, the authors use a number of spots distributed around the city so that when vehicles connect to them via Wi-Fi, they ...
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