In this paper, a new method based on genetic-fuzzy algorithm for multi-objective optimization is proposed. This method is successfully applied to several multi-objective optimization problems. Two examples are presented: the first example is the optimization of two nonlinear mathematical functions and the second one is the design of PI controller for control of an induction motor drive supplie...

A Multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. For this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing exp...

The paper considers computational domains structured as a 3D grid of cells. It presents a cell-to-hypercube map that is useful for implementing the Alternating Direction Method (ADM). The map is shown to be perfectly load-balanced, and to optimally preserve adjacencies between cells in the computational domain.

This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 a...

mathematical modeling and simulation of microbial polyhydroxybutyrate (phb) production process is beneficial for optimization, design, and control purposes. in this study a batch model developed by mulchandani et al., [1] was used to simulate the process in matlab environment. it was revealed that the kinetic model parameters were estimated off the optimal or at a local optimal point. therefore...

As a system scientist doing modeling and simulation, I have been interested for some time in ways that modeling and simulation and AI could be of value to each other. After all, both areas have their roots in putting knowledge into useful representations. I have speculated (AI Magazine, summer 1989, pp. 4348) that the scientist of the future, in applying computing to his(her) work, could benefi...

The engineering of cells for the production of fuels and chemicals involves simultaneous optimization of multiple objectives, such as specific productivity, extended substrate range and improved tolerance - all under a great degree of uncertainty. The achievement of these objectives under physiological and process constraints will be impossible without the use of mathematical modeling. However,...

optimal reactive power dispatch (orpd) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. due to the stochastic behavior of loads, the orpd requires a probabilistic mathematical model. in this paper, monte carlo simulation (mcs) is used for modeling of load uncertainties in the orpd problem. the problem is formulated as a nonlinear constrained mul...