In this paper we propose a mechanism for enhancing the performance of the Artificial Bee Colony Algorithm (ABCA) by making use low discrepancy Sobol sequence. The performance of the proposed Sobol sequence guided ABC (S-ABC) is analyzed over several benchmark functions and also compared to that of basic ABC. The empirical results show that the presence of low discrepancy sequence like that of S...

Nanotechnology involves the ability to see and control individual atoms and molecules which are about 100 nanometer or smaller. One of the major tools used in this field is atomic force microscopy which uses a wealth of techniques to measure the topography and investigates the surface forces in nanoscale. Friction force is the representation of the surface interaction between two surfaces an...

The estimation of variance-based importance measures (called Sobol’ indices) of the input variables of a numerical model can require a large number of model evaluations. It turns to be unacceptable for high-dimensional model involving a large number of input variables (typically more than ten). Recently, Sobol and Kucherenko have proposed the Derivative-based Global Sensitivity Measures (DGSM),...

Sensitivity analysis has been widely used for rational decision making of energy retrofit alternatives. A Sobol method is a variance based approach and provides powerful post-processing sensitivity results that enable to quantitatively identify influential and non-influential inputs. It can account for impacts of each input as well as impacts caused by all possible interactions between each inp...

Sobol indices are a widespread quantitative measure for variance-based global sensitivity analysis, but computing and utilizing them remains challenging for high-dimensional systems. We propose the tensor train decomposition (TT) as a unified framework for surrogate modeling and global sensitivity analysis via Sobol indices. We first overview several strategies to build a TT surrogate of the un...

This paper presents a new mutation operator called the Sobol Mutation (SOM) operator for enhancing the performance of Quantum Particle Swarm Optimization (QPSO) algorithm. The SOM operator unlike most of its contemporary mutation operators do not use the random probability distribution for perturbing the swarm population, but uses a quasi random Sobol sequence to find new solution vectors in th...

Direction numbers for generating Sobol′ sequences that satisfy the so-called Property A in up to 1111 dimensions have previously been given in Joe and Kuo [ACM Trans. Math. Software, 29 (2003), pp. 49–57]. However, these Sobol′ sequences may have poor two-dimensional projections. Here we provide a new set of direction numbers alleviating this problem. These are obtained by treating Sobol′ seque...

High-dimensional integrals are usually solved with Monte Carlo algorithms although theory suggests that low discrepancy algorithms are sometimes superior. We report on numerical testing which compares low discrepancy and Monte Carlo algorithms on the evaluation of nancial derivatives. The testing is performed on a Collateralized Mortgage Obligation (CMO) which is formulated as the computation o...

Variance-based sensitivity analysis has been performed for a study of input parameters contribution into output variability of a largescale air pollution model the Unified Danish Eulerian Model. The problem of computing of numerical indicators of sensitivity Sobol’ global sensitivity indices leads to multidimensional integration. Plain and Adaptive Monte Carlo techniques for numerical integrati...

Global sensitivity analysis of a numerical code, more specifically estimation of Sobol indices associated with input variables, generally requires a large number of model runs. When those demand too much computation time, it is necessary to use a reduced model (metamodel) to perform sensitivity analysis, whose outputs are numerically close to the ones of the original model, while being much fas...