Approximate local magnetic-to-electric surface
... Multipole Method (MFMM) [25, 43, 30, 29] and Krylov subspace solvers [57]. Of course, other approaches may be considered like for example asymptotic methods [4]. In all case, the success of a numerical method for studying high frequency scattering is based on the fact that the method is stable and w ...
... Multipole Method (MFMM) [25, 43, 30, 29] and Krylov subspace solvers [57]. Of course, other approaches may be considered like for example asymptotic methods [4]. In all case, the success of a numerical method for studying high frequency scattering is based on the fact that the method is stable and w ...
Solving the 0-1 Knapsack Problem with Genetic Algorithms
... In the implementation of the program, we tried two selection methods: roulette-wheel and group selection, combined with elitism, where two of the fittest chromosomes are copied without changes to the new population, so the best solutions found will not be lost. Roulette-wheel selection Roulette-whee ...
... In the implementation of the program, we tried two selection methods: roulette-wheel and group selection, combined with elitism, where two of the fittest chromosomes are copied without changes to the new population, so the best solutions found will not be lost. Roulette-wheel selection Roulette-whee ...
RWA Problem formulations
... Network topology: number of Nodes, Links Matrix An optional constraint on the number of wavelengths. We are required to determine the different light paths to be established, the routes over which they are set up and also determine the wavelengths that should be assigned to these lightpaths so t ...
... Network topology: number of Nodes, Links Matrix An optional constraint on the number of wavelengths. We are required to determine the different light paths to be established, the routes over which they are set up and also determine the wavelengths that should be assigned to these lightpaths so t ...
2.4 Differences Between Linear and Nonlinear Equations
... Last Time: We developed 1st Order ODE models for physical systems and solved them using the methods of Integrating Factor and Separable Equations. In Section 1.3 we noted three common questions we would be concerned with this semester. 1. (Existence) Given an IVP, does a solution exist? 2. (Uniquene ...
... Last Time: We developed 1st Order ODE models for physical systems and solved them using the methods of Integrating Factor and Separable Equations. In Section 1.3 we noted three common questions we would be concerned with this semester. 1. (Existence) Given an IVP, does a solution exist? 2. (Uniquene ...
Chapter 26 Capacitance and Dielectrics. Solutions of
... Some physical systems possessing capacitance continuously distributed over space can be modeled as an infinite array of discrete circuit elements. Examples are a microwave waveguide and the axon of a nerve cell. To practice analysis of an infinite array, determine the equivalent capacitance C betwee ...
... Some physical systems possessing capacitance continuously distributed over space can be modeled as an infinite array of discrete circuit elements. Examples are a microwave waveguide and the axon of a nerve cell. To practice analysis of an infinite array, determine the equivalent capacitance C betwee ...
Solutions of Smooth Nonlinear Partial Differential Equations
... 6 has to date not been obtained in any of the usual theories of generalized solutions of linear and nonlinear PDEs. Indeed, and perhaps as a result of the insufficiency of the spaces of generalized functions that are typical in the study of generalized solutions of PDEs, at least from the point of vi ...
... 6 has to date not been obtained in any of the usual theories of generalized solutions of linear and nonlinear PDEs. Indeed, and perhaps as a result of the insufficiency of the spaces of generalized functions that are typical in the study of generalized solutions of PDEs, at least from the point of vi ...
A Fictitious Time Integration Method for a Quasilinear Elliptic
... to let the circumferential grid points locate on the boundary. However, this may complicate the numerical computation for arbitrary plane domain. Because the boundary condition is given on the contour Γ, not on the boundary of the rectangle Ω̄, we require to derive the governing equations of these u ...
... to let the circumferential grid points locate on the boundary. However, this may complicate the numerical computation for arbitrary plane domain. Because the boundary condition is given on the contour Γ, not on the boundary of the rectangle Ω̄, we require to derive the governing equations of these u ...
CLASSICAL RESULTS VIA MANN–ISHIKAWA ITERATION
... with t0 , b, τ ∈ R, τ > 0, f ∈ C([t0 , b] × R2 , R). The existence of an approximative solution for equation (1) is given by theorem 1 from [1] (see also [2], [6], [5]). The proof of this theorem is based on the contraction principle. We shall prove it here by applying Mann iteration. In the last de ...
... with t0 , b, τ ∈ R, τ > 0, f ∈ C([t0 , b] × R2 , R). The existence of an approximative solution for equation (1) is given by theorem 1 from [1] (see also [2], [6], [5]). The proof of this theorem is based on the contraction principle. We shall prove it here by applying Mann iteration. In the last de ...
Quadratic optimization over a second-order cone with linear equality
... cones using linear matrix inequalities (LMIs) [22]. Consequently, polynomial-time interior-point algorithms [15] become applicable for this type of problems. For a general nonhomogeneous quadratic programming problem over a second-order cone, Jin et al. [14] provided an exact computable representati ...
... cones using linear matrix inequalities (LMIs) [22]. Consequently, polynomial-time interior-point algorithms [15] become applicable for this type of problems. For a general nonhomogeneous quadratic programming problem over a second-order cone, Jin et al. [14] provided an exact computable representati ...
Multiple-criteria decision analysis
Multiple-criteria decision-making or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly considers multiple criteria in decision-making environments. Whether in our daily lives or in professional settings, there are typically multiple conflicting criteria that need to be evaluated in making decisions. Cost or price is usually one of the main criteria. Some measure of quality is typically another criterion that is in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider. It is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, we are interested in getting high returns but at the same time reducing our risks. Again, the stocks that have the potential of bringing high returns typically also carry high risks of losing money. In a service industry, customer satisfaction and the cost of providing service are two conflicting criteria that would be useful to consider.In our daily lives, we usually weigh multiple criteria implicitly and we may be comfortable with the consequences of such decisions that are made based on only intuition. On the other hand, when stakes are high, it is important to properly structure the problem and explicitly evaluate multiple criteria. In making the decision of whether to build a nuclear power plant or not, and where to build it, there are not only very complex issues involving multiple criteria, but there are also multiple parties who are deeply affected from the consequences.Structuring complex problems well and considering multiple criteria explicitly leads to more informed and better decisions. There have been important advances in this field since the start of the modern multiple-criteria decision-making discipline in the early 1960s. A variety of approaches and methods, many implemented by specialized decision-making software, have been developed for their application in an array of disciplines, ranging from politics and business to the environment and energy.