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Showing 13 results for Optimal Design

M.h. Afshar, M.r. Ghasemi,
Volume 3, Issue 2 (6-2005)
Abstract

An efficient selection operator for use in genetic search of pipe networks optimal design is introduced in this paper. The proposed selection scheme is the superior member of a family of improved selection operators developed in an attempt to more closely simulate the main features of the natural mating process which is not reflected in existing selection schemes. The mating process occurring in the nature exhibits two distinct features. First, there is a competition between phenotypes looking for the fittest possible mate which usually ends up with choosing a mate with more or less the same fitness. Second, and more importantly, the search for a mate is often confined to a community of phenotypes rather than the whole population. Four different selection operators simulating these features in a random and pre-determined manner are developed and tested. All the selection schemes exhibit good convergence characteristics, in particular the one in which both the size of the sub-community and the pair of the mates in the sub-community are determined randomly. The efficiency of the proposed selection operator is shown by applying the method for the optimal design of three well-known benchmark networks, namely two-loop, Hanoi and New-York networks. The proposed scheme produces results comparable to the best results presented in the literature with much less computational effort
H. Moharrami, S.a. Alavinasab,
Volume 4, Issue 2 (6-2006)
Abstract

In this paper a general procedure for automated minimum weight design of twodimensional steel frames under seismic loading is proposed. The proposal comprises two parts: a) Formulation of automated design of frames under seismic loading and b) introduction of an optimization engine and the improvement made on it for the solution of optimal design. Seismic loading, that depends on dynamic characteristics of structure, is determined using "Equivalent static loading" scheme. The design automation is sought via formulation of the design problem in the form of a standard optimization problem in which the design requirements is treated as optimization constraints. The Optimality Criteria (OC) method has been modified/improved and used for solution of the optimization problem. The improvement in (OC) algorithm relates to simultaneous identification of active set of constraints and calculation of corresponding Lagrange multipliers. The modification has resulted in rapid convergence of the algorithm, which is promising for highly nonlinear optimal design problems. Two examples have been provided to show the procedure of automated design and optimization of seismic-resistant frames and the performance and capability of the proposed algorithm.
M.h. Afshar, R. Rajabpour,
Volume 5, Issue 4 (12-2007)
Abstract

This paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. The model makes use of the newly introduced particle swarm optimization algorithm. A two step optimization model is developed and solved with the particle swarm optimization method. The model first carries out an exhaustive enumeration search for all feasible sets of pump combinations able to cope with a given demand curve over the required period. The particle swarm optimization algorithm is then called in to search for optimal operation of each set. Having solved the operation problem of all feasible sets, one can calculate the total cost of operation and depreciation of initial investment for all the sets and the optimal set and the corresponding operating policy is determined. The proposed model is applied to the design and operation of a real-world irrigation pumping system and the results are presented and compared with those of a genetic algorithm. The results indicate that the proposed mode in conjunction with the particle swarm optimization algorithm is a versatile management model for the design and operation of real-world irrigation pumping systems.
M.h. Afshar, A. Afshar, M. A. Mariño, Hon. M. Asce,
Volume 7, Issue 2 (6-2009)
Abstract

This paper presents the application of an iterative penalty method for the design of water distribution pipe networks. The optimal design of pipe networks is first recasted into an unconstrained minimization problem via the use of the penalty method, which is then solved by a global mathematical optimization tool. The difficulty of using a trial and error procedure to select the proper value of the penalty parameter is overcome by an iterative use of the penalty parameter. The proposed method reduces the original problem with a priori unknown penalty parameter to a series of similar optimization problems with known and increasing value of the penalty parameters. An iterative use of the penalty parameter is then implemented and its effect on the final solution is investigated. Two different methods of fitting, namely least squares and cubic splines, are used to continuously approximate the discrete pipe cost function and are tested by numerical examples. The method is applied to some benchmark examples and the results are compared with other global optimization approaches. The proposed method is shown to be comparable to existing global optimization methods.
A. Kaveh, O. Sabzi,
Volume 10, Issue 3 (9-2012)
Abstract

In this paper a discrete Big Bang-Big Crunch algorithm is applied to optimal design of reinforced concrete planar frames under

the gravity and lateral loads. Optimization is based on ACI 318-08 code. Columns are assumed to resist axial loads and bending

moments, while beams resist only bending moments. Second-order effects are also considered for the compression members, and

columns are checked for their slenderness and their end moments are magnified when necessary. The main aim of the BB-BC

process is to minimize the cost of material and construction of the reinforced concrete frames under the applied loads such that

the strength requirements of the ACI 318 code are fulfilled. In the process of optimization, the cost per unit length of the sections

is used for the formation of the subsequent generation. Three bending frames are optimized using BB-BC and the results are

compared to those of the genetic algorithm.


A. Kaveh, M. Farahani, N. Shojaei,
Volume 10, Issue 4 (12-2012)
Abstract

Barrel vaults are attractive space structures that cover large area without intermediate supports. In this paper, the charged

search system (CSS) optimization algorithm is employed for optimal design of barrel vaults. This method utilizes the governing

laws of Coulomb and Gauss from electrostatics and the Newtonian law of mechanics. The results demonstrate the efficiency of

the discrete CSS algorithm compared to other meta-heuristic algorithms.


K. J. Tu, Y. W. Huang,
Volume 11, Issue 4 (12-2013)
Abstract

The decisions made in the planning phase of a building project greatly affect its future operation and maintenance (O&M) cost. Recognizing the O&M cost of condominiums’ common facilities as a critical issue for home owners, this research aims to develop an artificial neural network (ANN) O&M cost prediction model to assist developers and architects in effectively assessing the impacts of their decisions made in the planning phase of condominium projects on future O&M costs. A regression cost prediction model was also developed as a benchmark model for testing the predictive accuracy of the ANN model. Six critical building design attributes (building age, number of apartment units, number of floors, average sale price, total floor area, and common facility floor area) which are usually available in the project planning phase, were identified as the input factors to both models and average monthly O&M cost as the output factor. 55 of the 65 existing condominium properties randomly selected were treated as the training samples whose data were used to develop the ANN and regression models the other ten as the test samples to compare and verify the predictive performance of both models. The study results revealed that the ANN model delivers more accurate and reliable cost prediction results, with lower average absolute error around 7.2% and maximum absolute error around 16.7%, as compared with the regression model. This study shows that ANN is an effective method in predicting building O&M costs in the project planning phase. Keywords: Project management, Facility management, Common facilities, Cost modeling.
H. Rahami, A. Kaveh, M. Ardalan Asl, S. R. Mirghaderi,
Volume 11, Issue 4 (12-2013)
Abstract

In the process of structural analysis we often come to structures that can be analyzed with simpler methods than the standard approaches. For these structures, known as regular structures, the matrices involved are in canonical forms and their eigen-solution can be performed in a simple manner. However, by adding or removing some elements or nodes, such methods cannot be utilized. Here, an efficient method is developed for the analysis of irregular structures in the form a regular structure with additional or missing nodes or with additional or missing supports. In this method, the saving in computational time is considerable. The power of the method becomes more apparent when the analysis should be repeated very many times as it is the case in optimal design or non-linear analysis.
M. Abbasi, A. H. Davaei Markazi,
Volume 12, Issue 1 (3-2014)
Abstract

An important factor in the design and implementation of structural control strategies is the number and placement of actuators. By employing optimally-located actuators, the effectiveness of control system increases, while with an optimal number of actuators, an acceptable level of performance can be achieved with fewer actuators. The method proposed in this paper, simultaneously determines the number and location of actuators, installed in a building, in an optimal sense. In particular, a genetic algorithm which minimizes a suitably defined structural damage index is introduced and applied to a well-known nonlinear model of a 20-story benchmark building. It is shown in the paper that an equal damage protection, compared to the work of other researchers, can be achieved with fewer numbers of optimally placed actuators. This result can be important from economic point of view. However, the attempt to minimize one performance index has negative effect on the others. To cope with this problem to some extent, the proposed genetic methodology has been modified to be applied in a multi-objective optimization problem.
A. Gholizad, P. Kamrani Moghaddam,
Volume 12, Issue 1 (3-2014)
Abstract

High performance and reliability of refurbish able knee braced steel frames has been confirmed in previous researches trying to get an optimal design for its configuration. Buckling of diagonal member which affects the hysteretic behavior of KBF under cyclic loadings has not been foreseen in previous evaluations of this system. This deficiency can be improved by utilization of adjustable rotary friction damper device (FDD) as knee element. Diagonal element buckling can be prevented considering a suitable value for FDD sliding threshold moment Mf. Lower values of Mf Lower energy dissipation rate in FDD and this leads to an optimization problem. Nonlinear time history analyses have been performed in addition to lateral cyclic loading analyses to evaluate the response of single story KBF subjected to seismic excitation. Optimal Mf in FDD has been chosen according to these analyses results. Roof displacement and acceleration, base shear and diagonal element’s buckling status have been compared in optimally designed KBF and FDD utilized KBF (FKBF) with different configurations. Nonlinear dynamic analyses have been performed for one, four, eight and twelve story frames under different seismic records with several PGAs. More than 60% displacement response reduction has been earned for the FKBF without considerable increase in base shear.
A. Kaveh, A. Nasrolahi,
Volume 12, Issue 1 (3-2014)
Abstract

In this paper, a new enhanced version of the Particle Swarm Optimization (PSO) is presented. An important modification is made by adding probabilistic functions into PSO, and it is named Probabilistic Particle Swarm Optimization (PPSO). Since the variation of the velocity of particles in PSO constitutes its search engine, it should provide two phases of optimization process which are: exploration and exploitation. However, this aim is unachievable due to the lack of balanced particles’ velocity formula in the PSO. The main feature presented in the study is the introduction of a probabilistic scheme for updating the velocity of each particle. The Probabilistic Particle Swarm Optimization (PPSO) formulation thus developed allows us to find the best sequence of the exploration and exploitation phases entailed by the optimization search process. The validity of the present approach is demonstrated by solving three classical sizing optimization problems of spatial truss structures.
Mohammadreza Sheidaii, Mehdi Babaei,
Volume 15, Issue 2 (3-2017)
Abstract

Engineering design usually requires considering multiple variances in a design and integrating them appropriately in order to achieve the most desirable alternative. This consideration takes particular importance in the constructional projects of civil engineering. However, frequently, the structural designer’s considerations in civil engineering teams contrast the stylish and creative novelties of architectures. Then, we should take up new methodologies to yield appropriate alternatives which meet artistic aspects of design and simultaneously satisfy the structural designer’s demands. Consequently, the process of design should incorporate the multi-fold aspects of engineer’s requirements and their personal preference. So, in this study, we preset a systematic approach, so-called desirability based design, to perform a directed multi-objective optimal design considering various aspects of a design, based on soft-computing methods. Fuzzy logic integrated with genetic algorithm is employed to build a decision-making fuzzy system based on expert knowledge. It will be employed to conduct the designing process. Illustrative examples show practicality and efficiency of the presented methodology in structural design of several space structures.


Jalal Akbari , Mohammad Sadegh Ayubirad ,
Volume 15, Issue 2 (3-2017)
Abstract

From practical point of view, optimum design of structures under time variable loadings faces many challenges. Issues such as time-dependent behavior of constraints and the computational costs of the gradients could be mentioned. In order to prevent such difficulties, in this paper, response spectrum method has been utilized instead of applying direct time history method. Additionally, seismic design of structures is defined as a design for a specific response spectra not for an individual acceleration time history. Furthermore, here, in order to guarantee the global optimal designs, the obtained results from gradient-based method are compared with those from the discrete optimization technique (Genetic algorithm). As well, the P-Delta effects are considered in a seismic analysis. In addition, many practical constraints according to the Iranian national building code (NBC) are included in the optimization problem. The developed MATLAB based computer program is utilized to solve the numerical examples of low, intermediate and relatively high-rise braced and un-braced steel frames.



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