This article considers the efficiency of event-related fMRI designs in terms of the optimum temporal pattern of stimulus or trial presentations. The distinction between "stochastic" and "deterministic" is used to distinguish between designs that are specified in terms of the probability that an event will occur at a series of time points (stochastic) and those in which events always occur at pr...

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two powerful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the derivatives of the objective function is unnecessa...

A new two-pump fiber optical parametric amplifier (FOPA) is presented, which is composed of two-section high nonlinear fibers (HNLFs). Genetic algorithm (GA), a multivariate stochastic optimization algorithm is applied to optimize parameters of two fiber segments, such as the length and dispersion coefficient of fiber. A broadband FOPA with twosection HNLFs is obtained using optimum design para...

This paper present work on modern control approaches in titling railway vehicles. The design of the Linear Quadratic Gaussian with integral action controller provides the required tilt compensation, while the addition of the fuzzy mechanism to the controller improves the system performance both for the deterministic and stochastic track. Moreover, the use of multiobjective GA as a tuning method...

This paper describes a methodology for solving Parameter Design (PD) problems in production and business systems of considerable complexity. The solution is aimed at determining optimum settings to system critical parameters so that each system response is at its optimum performance level with least amount of variability. When approaching such problem, analysts are often faced with four major c...

Various methods have been used to economically design wastewater and stormwater collection systems. In this article, Discrete Differential Dynamic Programming (DDDP) which is a subsection of dynamic programming (DP) was used. For each pipe network, various alternatives such as depth and slope of pipe laying and various diameters could be considered to satisfy hydraulic and engineering constrain...

We present new conditions for the strong consistency and asymptotic normality of the least squares estimator in nonlinear stochastic models when the design variables vary in a finite set. The application to self-tuning optimisation is considered, with a simple adaptive strategy that guarantees simultaneously the convergence to the optimum and the strong consistency of the estimates of the model...

We demonstrate how the stochastic global optimization scheme of Simulated Annealing can be used to evaluate optimum parameters in the problem of DNA breathing dynamics. The breathing dynamics is followed in accordance with the stochastic Gillespie scheme with the denaturation zones in double stranded DNA studied as a single molecule time series. Simulated Annealing is used to find the optimum v...

Determining the optimum number of suppliers and the optimum quantities to order from each of them is a critical problem for any supply chain. This paper has mathematically arrived at conditions to identify the appropriate sourcing strategy in a multi-period scenario for a stochastic supply and a stochastic demand environment. It has also obtained the total order quantity, optimum number of supp...