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Performing online feature subset selection (OFS) when data samples arrive at a high velocity in a time-dependent manner is a critical problem to solve. The situation becomes more difficult when the features also arrive in a stream. Several efforts were ...

In a first-of-its-kind study, we propose an online feature selection (OFS) framework for streaming data under big data paradigm, by proposing (i) parallel hybrid particle swarm optimization (PSO)-based wrapper, (ii) a robust method to handle high ...

In a local search algorithm, one of its most important features is the definition of its neighborhood which is crucial to the algorithm’s performance. In this paper, we present an analysis of neighborhood combination search for solving the single-...

To solve the strategic flight schedule optimization problem for multiple airport and multiple operation days, a two-stage stochastic programming model is established. Flight schedule optimization is made in the first stage of the model, and the tactical ...

Scheduling in the real-world has to be performed under significant uncertainty. This uncertainty can be introduced into mathematical optimization by using two-stage stochastic optimization, where the uncertainty is modeled by a discrete set of scenarios,...

A speed trajectory profile indicating the authorized train speed at each position can be used to guide the driver or the automatic train operation (ATO) system to operate the train more efficiently, which is the most important part of the Chinese Train ...

Hybrid evolutionary algorithms have been successfully applied to solve numerous multiobjective optimization problems (MOP). In this paper, a new hybrid evolutionary approach based on search strategy adaptation (HESSA) is presented. In HESSA, the search ...

This paper presents the hybrid approach of Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) for global optimization. In standard ICA, there are only two types of countries: imperialists and colonies. In the proposed hybrid ...

In this paper, two-way differential evolution algorithm is proposed according to two different hybrid scheme of differential evolution algorithm. The bin and exp hybrid scheme are run at same time is the key operation of new algorithm, and regard the ...

This paper proposes an orthogonal mutation technology, which combines the orthogonal initialization technology and the orthogonal crossover technique. They are called the orthogonal processing technologies. The fusion of the differential evolution ...

This work discusses how Radial Basis Function (RBF) neural networks can have their free parameters defined by evolutionary algorithms (EAs). For such, it firstly presents an overall view of the problems involved and the different evolutionary approaches ...

The paper proposes a unified direct approach to a number of problems arising in image processing. In particular, the areas of image registration, and object or pattern recognition are addressed when the images of interest display significant geometric ...

A mechanism involving evolutionary genetic programming (GP) and the expectation maximization algorithm (EM) is proposed to generate feature functions, based on the primitive features, for an image pattern recognition system on the diagnosis of the ...

This paper presents a hybrid evolutionary algorithm to tackle university course timetabling problems. The proposed approach is an extension of a non-linear great deluge algorithm in which evolutionary operators are incorporated. First, we generate a ...

This paper proposes a hybrid evolutionary algorithm based radial basis function neural network (RBFnn) for sales forecasting. The proposed hybrid of particle swarm and genetic algorithm based optimization (HPSGO) algorithm gathers virtues of particle ...