Top PDF Hybrid evolutionary algorithms for the TSP
A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
... where the points at which crossover is allowed to cut and splice material, is ...adapted. The mechanism appends an additional L bits to each individuals, which is used to determine crossover points at each ...
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Enhancing evolutionary algorithms through recombination and parallelism
... schemes for an island model. All of them are an effort to decrease the risk of premature ...parameter for incoming ...with the best and worst global individuals and population mean ...
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Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
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Migrants Selection and Replacement in Distributed Evolutionary Algorithms for Dynamic Optimization
... studied the influence of the migration poli- cies in stationary ...showed the benefits of sending a random individual instead of the best ...approaches for DOPs have used migration ...
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Enhancing evolutionary algorithms through recombination and parallelism
... mechanisms. The use of multiple crossovers on multiple parents (MCMP) proved to be efficient in single and multiple objective optimization and behaves better than previous ...increasing the risk of ...
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An efficient constraint handling methodology for multi-objective evolutionary algorithms
... approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal ...methodology for solving COP using a multi- objective strategy is used. In the ...
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Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms
... 6 the results obtained are presented as improvement percentages when vehicles are being routed according to the strate- gies analyzed here instead of following the flows obtained from the ...
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Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines
... parallelize the individuals’ evaluation. In each iteration, the algorithm adds the best product to the test suite until all weighted pairs are ...covered. The best product to be added ...
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An Analysis of a Hybrid Evolutionary Algorithm by means of its Phylogenetic Information
... ABSTRACT— The study conducted in this work analyses the interactions between different Evolutionary Algorithms when they are ...hybridized. For this purpose, the phylogenetic ...
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Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
... [29]. The job shop scheduling problem (JSSP) is related to the allocation of limited resources (machines) to jobs over ...goal the optimization of one or more objectives. The model considered ...
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Melomics: A Case-Study of AI in Spain
... characteristics, evolutionary algorithms with well-engineered indirect encodings can obtain complex solutions, and potentially generate complex variations of these ...or the arts), these ...
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Optimization of distribution networks using evolutionary algorithms
... 6.3 the algorithm starts from scratch, taking the GPS points from CM1 to propose, initially, random ...In the following generations, the GA algo- rithm learns and proposes better ...
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Hybrid algorithms for solving routing problems
... framework. The first operator introduced is inspired by ideas from Shaw's LNS ...[161]. The algorithm removes first, randomly, a subset of customers with a bias toward customers generating the ...
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Solving the single machine scheduling problem with sequence-dependent set-up times as a TSP via evolutionary algorithms
... an evolutionary algorithm based on a special inver- over operator, which incorporates the knowledge taken from other individual in the ...population. The operator is a mixture of inversion and ...
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Advances in Hybrid Evolutionary Computation for Continuous Optimization
... population, the hybridization process and the performance of the algorithms in past executions to infer a model that characterizes the best performing algorithm at each state of ...
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New hybrid neuro evolutionary algorithms for renewable energy and facilities management problems
... tackle the complexity of the physical equations, which rule the atmosphere to obtain a prediction); and (2) statistical approaches (usually data-driven models to obtain ...predictions). The ...
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Automatically Modeling Hybrid Evolutionary Algorithms from Past Executions
... For analyzing the results, the following algorithms were executed over the benchmark: the DE algorithm, the ñrst local search of the MTS algorithms (LSI), a randomHRH algorithm which, [r] ...
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