Biased random key genetic algorithmsArtificial Neural Network optimizationTime seriesArtificial Neural Networks (ANN) is one of the most used methods in time series forecasting. Mostly, it is hard to determine the design and weight parameters of ANNs by experience. For this reason, ANN optimization ...
This paper presents a biased random-key genetic algorithm designed to solve the open vehicle routing problem with capacity and distance constraints. Consider a depot from which vehicles depart to deliver goods demanded by clients. Every client is served by one vehicle that is part of a homogeneous...
Ribeiro, A biased random-key genetic algorithm for routing and wavelength assignment, Journal of Global Optimization, v.50 n.3, p.503-518, July 2011T. Noronha, M. Resende and C. Ribeiro , "A biased random-key genetic algorithm for routing and wavelength assignment" , J. Global. ...
We present a biased random-key genetic algorithm for approximately solving the problem of routing and wavelength assignment of sliding scheduled lightpath demands in optical networks. In this problem variant, each demand is characterized not only by a source and a destination, but also by a ...
ARandom-KeyGeneticAlgorithmfortheGeneralizedTraveling SalesmanProblem LawrenceV.Snyder ∗ DepartmentofIndustrialandSystemsEngineering LehighUniversity 200WestPackerAvenue,MohlerLab Bethlehem,PA,18015USA larry.snyder@lehigh.edu MarkS.Daskin DepartmentofIndustrialEngineeringandManagementSciences ...
FlowshopschedulingBiasedrandom-keygeneticalgorithmMetaheuristicsabstractInthispaper,weadvancethestateoftheartforsolvingthePermutationFlowshopSchedulingProblemwithtotalflowtimeminimization.Forthispurpose,weproposeaBiasedRandom-KeyGeneticAlgorithm(BRKGA)introducingonitanewfeaturecalledshaking.Withtheshaking,insteadtofullreset...
Therefore, the promotion and development of mmWave technology in the construction process of 5G network will become the key. Propagation characteristics When an electromagnetic wave travels in free space, its path is a ray between the transceiver. According to the free-space transmission model, the...
The key contributions are as follows: HPM utilizes a Ranker-based and SMOTE-based feature selection, which helps to select only essential features from the dataset and overcome data Imbalancing. It improves the overall performance of the model. This research also overcomes the limitation of the ...
{3} )was previously analyzed using visualization methods [36]. We demonstrate that the RANSAC algorithm filters the sample space from noisy data (i.e., outliers), automatically selects descriptors previous shown to correlate with key PV properties and generates models with good predictive statistics...
This paper presents a multi-population biased random-key genetic algorithm (BRKGA) for the single container loading problem (3D-CLP) where several rectangular boxes of different sizes are loaded into a single rectangular container. The approach uses a maximal-space representation to manage the free...