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Open-shop scheduling problems are highly complex (NP-Hard), where solution is represented by a permutation of machines order that each job must follow to be processed, and for each job, it can have a different machines order. The main goal in these problems is to reduce consumption resources, and at same time, improving several performance criteria. In this work we propose a computational strategy...
There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The proposal uses probability density function according to best of initial population to sample new population and save better individuals iteratively. Then using centroid...
Gray-Box Models which combine a phenomenological model with a black box tool are useful for determining the values of not well known parameters of the model. In this work an indirect strategy for training these gray box models using least-square support vector machine and genetic algorithms is presented. The gray box model was tested in a Continuous Stirred Tank Reactor process with good results (Index...
The Haitian Republic currently does not have a suitable telecommunication network to support the novel information technologies in all the principal cities of the country. Therefore, it is a real concern to design an appropriate telecommunication infrastructure to cover all the national territory aiming to support the offer of these services in the country. The optical networks of Digicel and Natcom...
This work presents the modeling and implementation of a Hybrid Chemical Reactions Optimization that uses CRO operators to find good solutions, and heuristics to initialize the first population and mapping tasks in processors to solve the Multiprocessor task scheduling problem, taking into account the heterogeneity of the multiprocessor system.
Artificial Immune Systems are nature inspired techniques which have been applied with success to several areas. The Clonal Selection Algorithm (CLONALG) is one of the most used immune inspired techniques for optimization. Similarly to other metaheuristics, CLONALG requires a large number of objective function evaluations making it impracticable when the objective function is computationally expensive...
The last decade Digital Pathology is coming as a relevant and promising area for cancer research and clinical practice thanks to two main trends, 1) the availability of whole slide scanners for complete pathology slide digitalization, and 2) the development of several computational method for histopathology image analysis. However, there are very few works addressed to analyze the whole-slide digitized...
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