Proper selection of variables is necessary when dealing with large number of input dimensions in regression problems. In the paper, we investigate the behaviour of landscape that is formed when using Delta test as the optimization criterion. We show that simple and greedy Forward-backward selection procedure with multiple restarts gives optimal results for data sets with large number of samples...

In emergency rescue operations, it is very important for management to arrange materials scientifically and reasonably according needs. However, the decision criteria material distribution are often diverse, coupled with lack of information acquisition due suddenness development complexity disasters, which makes scientific decisions about face great challenges. This paper proposes a multi-crite...

Magnetic resonance imaging (MRI) is a powerful tool for clinical diagnosis because it allows to distinguish different tissues and allows multiple modalities (T1, T2, ...) each having particular properties. In this work, the segmentation of MR Brain images is considered as an optimization problem and solved using evolutionary algorithms: particle swarm optimization (PSO) and differential evoluti...

In this paper, a generic methodology based on swarm algorithms using Artificial Bee Colony (ABC) algorithm is proposed for combined cost and weight optimization of laminated composite structures. Two approaches, namely Vector Evaluated Design Optimization (VEDO) and Objective Switching Design Optimization (OSDO), have been used for solving constrained multi-objective optimization problems. The ...

1. Abstract The purpose of this study is to develop a practicable method for multiple-constrained optimization problems. In real-world optimization problems, the complexity of design space depends on their formulation. Thus, in order to search useful solutions within feasible computational time, the simplicity of applications is necessary for the technique of constraint satisfaction. The propos...

Sequential sampling strategies based on Gaussian processes are now widely used for the optimization of problems involving costly simulations. But Gaussian processes can also generate parallel optimization strategies. We focus here on a new, parameter free, parallel expected improvement criterion for asynchronous optimization. An estimation of the criterion, which mixes Monte Carlo sampling and ...

in this article, multiple-product pvrp with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. a mathematical formulation was provided for this problem. each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. to solve the problem, two meta-heuristic methods...