Determining an Economically Optimal (N,C) Design via Using Loss Functions

An Optimal Design Approach for Resistive and Inductive Superconducting Fault Current Limiters via MCDM Techniques

The design process of a superconducting current limiter (SFCL) requires simulation and definition of its electrical, magnetic and thermal properties in form of equivalent circuits and mathematical models. However, any change in SFCL parameters: dimension, resistance, and operating temperature can affect the limiting mode, quench time, and restore time. In this paper, following the simulation of...

THE EFFECTS OF INITIAL SAMPLING AND PENALTY FUNCTIONS IN OPTIMAL DESIGN OF TRUSSES USING METAHEURISTIC ALGORITHMS

Although Genetic algorithm (GA), Ant colony (AC) and Particle swarm optimization algorithm (PSO) have already been extended to various types of engineering problems, the effects of initial sampling beside constraints in the efficiency of algorithms, is still an interesting field. In this paper we show that, initial sampling with a special series of constraints play an important role in the conv...

On the Design Method of Economically Optimal Size of Projects

design of economically optimal double sampling design with zero acceptance numbers

in acceptance-sampling plans, the items of an incoming lot are inspected one by one. if the number of nonconforming items in sample is equal zero, the lot is accepted but if the number of nonconforming items is equal to one, then second sample is taken and the policy of zero acceptance number would be applied for the second sample. in this paper, a mathematical model is developed to design sing...

An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions

The generation of decision-theoretic Bayesian optimal designs is complicated by the significant computational challenge of minimising an analytically intractable expected loss function over a, potentially, high-dimensional design space. A new general approach for approximately finding Bayesian optimal designs is proposed which uses computationally efficient normal-based approximations to poster...

OPTIMAL ANALYSIS OF NON-REGULAR GRAPHS USING THE RESULTS OF REGULAR MODELS VIA AN ITERATIVE METHOD

In this paper an efficient method is developed for the analysis of non-regular graphs which contain regular submodels. A model is called regular if it can be expressed as the product of two or three subgraphs. Efficient decomposition methods are available in the literature for the analysis of some classes of regular models. In the present method, for a non-regular model, first the nodes of the ...