Time-history analysis based optimal design of space trusses: the CMA evolution strategy approach using GRNN and WA

Kaveh, A.,Fahimi-Farzam, M.,Kalateh-Ahani, M. Techno-Press 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.44 No.3

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

A new hybrid meta-heuristic for structural design: ranked particles optimization

Kaveh, A.,Nasrollahi, A. Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.2

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

Time-history analysis based optimal design of space trusses: the CMA evolution strategy approach using GRNN and WA

A. Kaveh,M. Fahimi-Farzam,M. Kalateh-Ahani 국제구조공학회 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.44 No.3

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

Optimum topology design of geometrically nonlinear suspended domes using ECBO

A. Kaveh,M. Rezaei 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.56 No.4

The suspended dome system is a new structural form that has become popular in the construction of long-span roof structures. Suspended dome is a kind of new pre-stressed space grid structure that has complex mechanical characteristics. In this paper, an optimum topology design algorithm is performed using the enhanced colliding bodies optimization (ECBO) method. The length of the strut, the cable initial strain, the cross-sectional area of the cables and the cross-sectional size of steel elements are adopted as design variables and the minimum volume of each dome is taken as the objective function. The topology optimization on lamella dome is performed by considering the type of the joint connections to determine the optimum number of rings, the optimum number of joints in each ring, the optimum height of crown and tubular sections of these domes. A simple procedure is provided to determine the configuration of the dome. This procedure includes calculating the joint coordinates and steel elements and cables constructions. The design constraints are implemented according to the provision of LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Constitution). This paper explores the efficiency of lamella dome with pin-joint and rigid-joint connections and compares them to investigate the performance of these domes under wind (according to the ASCE 7-05), dead and snow loading conditions. Then, a suspended dome with pin-joint single-layer reticulated shell and a suspended dome with rigid-joint single-layer reticulated shell are discussed. Optimization is performed via ECBO algorithm to demonstrate the effectiveness and robustness of the ECBO in creating optimal design for suspended domes.

A new PSRO algorithm for frequency constraint truss shape and size optimization

A. Kaveh,A. Zolghadr 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.3

In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

Seismic design of steel frames using multi-objective optimization

Kaveh, A.,Shojaei, I.,Gholipour, Y.,Rahami, H. Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.2

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

A new hybrid meta-heuristic for structural design: ranked particles optimization

A. Kaveh,A. Nasrollahi 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.2

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

Seismic design of steel frames using multi-objective optimization

A. Kaveh,I. Shojaei,Y. Gholipour,H. Rahami 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.45 No.2

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

Improved thermal exchange optimization algorithm for optimal design of skeletal structures

A. Kaveh,A. Dadras,T. Bakhshpoori 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.21 No.3

Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016\'s single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.

Improved thermal exchange optimization algorithm for optimal design of skeletal structures

Kaveh, A.,Dadras, A.,Bakhshpoori, T. Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.21 No.3

Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016's single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.