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Showing 2 results for Numerical Optimization

A. Nozari , H.e. Estekanchi,
Volume 1, Issue 2 (6-2011)
Abstract

Numerical simulation of structural response is a challenging issue in earthquake engineering and there has been remarkable progress in this area in the last decade. Endurance Time (ET) method is a new response history based analysis procedure for seismic assessment and structural design in which structures are subjected to a gradually intensifying dynamic excitation and their seismic performance is evaluated based on their responses at different excitation levels. Generating appropriate artificial dynamic excitation is essential in this type of analysis. In this paper, an optimization procedure is presented for computation of the intensifying acceleration functions utilized in the ET method and the results of this procedure are discussed. A set of the ET acceleration functions (ETAFs) is considered which has been produced utilizing numerical optimization considering 2048 acceleration points as optimization variables by an unconstrained optimization procedure. The ET formulation is then modified from the continuous time condition into the discrete time state thus the optimization problem is reformulated as a nonlinear least squares problem. In this way, a second set of the ETAFs is generated which better satisfies the proposed objective function. Subsequently, acceleration points are increased to 4096, for 40 seconds duration, and the third set of the ETAFs is produced using a multi level optimization procedure. Improvement of the ETAFs is demonstrated by analyzing several SDOF systems.
S. Carbas, M.p. Saka,
Volume 3, Issue 1 (3-2013)
Abstract

Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In order to overcome the various difficulties encountered in obtaining the solution of these problems, new techniques called metaheuristic algorithms are suggested. These techniques are numerical optimization algorithms that are based on a natural phenomenon. In this study, a state-of-art improved harmony search method with a new adaptive error strategy is proposed to handle the design constraints. Number of numerical examples is presented to demonstrate the efficiency of the proposed algorithm in solving engineering optimization problems.

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