B. Amaziane¹, A. Naji², D. Ouazar³, A. H.-D. Cheng⁴

CMC-Computers, Materials & Continua, Vol.2, No.2, pp. 85-96, 2005, DOI:10.3970/cmc.2005.002.085

Abstract In this paper the optimization of groundwater pumping in coastal aquifers under the threat of saltwater intrusion is investigated. The aquifer is inhomogeneous and contains several hydraulic conductivities zones. The aquifer data such as the hydraulic conductivities are uncertain, but with their expected mean and standard deviation values given. A stochastic boundary element method based on the perturbation technique is employed as the simulation tool. The stochastic optimization is handled by the chance-constrained programming. Genetic algorithm is selected as the optimization tool. Numerical examples of deterministic and stochastic problems are provided to demonstrate the feasibility More >

Z. Q. Zhu¹, Z. Liu¹, X. L. Wang¹, R. X. Yu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.6, No.6, pp. 567-576, 2004, DOI:10.3970/cmes.2004.006.567

Abstract To extend an available mono-objective optimization method to multi-objective/multi-disciplinary optimization, the construction of a suitable integral objective function (in gradient based deterministic method-DM) or fitness function (in genetic algorithm-GA) is important. An auto-adjusting weighted object optimization (AWO) method in DM is suggested to improve the available weighted sum method (linear combined weighted object optimizationLWO method). Two formulae of fitness function in GA are suggested for two kinds of design problems. Flow field solution is obtained by solving Euler equations. Electromagnetic field solution is obtained by solving Maxwell equations. Bi-disciplinary optimization computation is carried out by More >

A. Rama Mohan Rao¹, T.V.S.R. Appa Rao², B. Dattaguru³

CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.3, pp. 213-234, 2004, DOI:10.3970/cmes.2004.005.213

Abstract This paper presents an algorithm for automatic partitioning of unstructured meshes for parallel finite element computations employing float-encoded genetic algorithms (FEGA). The problem of mesh partitioning is represented in such a way that the number of variables considered in the genome (chromosome) construction is constant irrespective of the size of the problem. In order to accelerate the computational process, several acceleration techniques like constraining the search space, local improvement after initial global partitioning have been attempted. Finally, micro float-encoded genetic algorithms have been developed to accelerate the computational process. More >

B. Amaziane¹, A. Naji², D. Ouazar³

CMC-Computers, Materials & Continua, Vol.1, No.2, pp. 117-128, 2004, DOI:10.3970/cmc.2004.001.117

Abstract In this paper, a meshless method based on Radial Basis Functions (RBF) is coupled with genetic algorithms for parameter identification to some selected groundwater flow applications. The treated examples are generated by the diffusion equation with some specific boundary conditions describing the groundwater fluctuation in a leaky confined aquifer system near open tidal water. To select the best radial function interpolation and show the powerful of the method in comparison to domain based discretization methods, Multiquadric (MQ), Thin-Plate Spline (TPS) and Conical type functions are investigated and compared to finite difference results or analytical one. More >

R. Mathur¹, S. G. Advani², B. K. Fink³

CMES-Computer Modeling in Engineering & Sciences, Vol.4, No.5, pp. 587-602, 2003, DOI:10.3970/cmes.2003.004.587

Abstract Real number-coded hybrid genetic algorithms for optimal design of resin injection locations for the resin transfer molding process are evaluated in this paper. Resin transfer molding (RTM) is widely used to manufacture composite parts with material and geometric complexities, especially in automotive and aerospace sectors. The sub-optimal location of the resin injection locations (gates) can leads to the formation of resin starved regions and require long mold fill times, thus affecting the part quality and increasing manufacturing costs. There is a need for automated design algorithms and software that can determine the best gate and… More >

Al Globus¹, Madhu Menon², Deepak Srivastava¹

CMES-Computer Modeling in Engineering & Sciences, Vol.3, No.5, pp. 557-574, 2002, DOI:10.3970/cmes.2002.003.557

Abstract A genetic algorithm procedure has been developed for fitting parameters for many-body interatomic force field functions. Given a physics or chemistry based analytic form for the force field function, parameters are typically chosen to fit a range of structural and physical properties given either by experiments and/or by higher accuracy tight-binding or ab-initio simulations. The method involves using both near equilibrium and far from equilibrium configurations in the fitting procedure, and is unlikely to be trapped in local minima in the complex many-dimensional parameter space. As a proof of concept, we demonstrate the procedure for… More >

R. Mustata¹, S. D. Harris², L. Elliott¹, D. Lesnic¹, D. B. Ingham¹

CMES-Computer Modeling in Engineering & Sciences, Vol.1, No.3, pp. 107-116, 2000, DOI:10.3970/cmes.2000.001.409

Abstract An inverse boundary element method is developed to characterise the components of the hydraulic conductivity tensor K of anisotropic materials. Surface measurements at exposed boundaries serve as additional input to a Genetic Algorithm (GA) using a modified least squares functional that minimises the difference between observed and BEM-predicted boundary pressure and/or hydraulic flux measurements under current hydraulic conductivity tensor component estimates. More >