Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous global optimization. Over the last few decades, DE has often been employed for solving various engineering problems. At the same time, the DE structure has some limitations in the complicated problems. This fact has inspired many researchers to improve on DE by proposing modifications to the original algo...

Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous global optimization. Over the last few decades, DE has often been employed for solving various engineering problems. At the same time, the DE structure has some limitations in the complicated problems. This fact has inspired many researchers to improve on DE by proposing modifications to the original algo...

‎This paper presents an application of partial differential equations(PDEs) for the segmentation of abdominal and thoracic aortic in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been exte...

Semilinear stochastic evolution equations with multiplicative L'evy noise are considered‎. ‎The drift term is assumed to be monotone nonlinear and with linear growth‎. ‎Unlike other similar works‎, ‎we do not impose coercivity conditions on coefficients‎. ‎We establish the continuous dependence of the mild solution with respect to initial conditions and also on coefficients. ‎As corollaries of ...

Nowadays, numerical models have great importance in every field of science, especially for solving the nonlinear differential equations, partial differential equations, biochemical reactions, etc. The total time evolution of the reactant concentrations in the basic enzyme-substrate reaction is simulated by the Runge-Kutta of order four (RK4) and by nonstandard finite difference (NSFD) method. A...

The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum solutions of complex optimization problems. A promising new evolutionary algorithm, differential evolution, has garnered significant attention in the engineering optimization research. Differential evolution has the advantage of incorporating a relatively simple and efficient form of mutation and...