Optimum Design of Gravity and Reinforced Retaining Walls using Enhanced Charged System Search Algorithm

S. Talatahari,R. Sheikholeslami 대한토목학회 2014 KSCE JOURNAL OF CIVIL ENGINEERING Vol.18 No.5

This paper develops a methodology to obtain the optimum design of the gravity and reinforced cantilever retaining walls in terms of least-cost, having different cases of backfill satisfying the stability criteria, according to the height and properties of earth that the wall are required to support. An Enhanced Charged System Search Algorithm (ECSS) is utilized to find the economical sections as the output after minimizing the cost. The ECSS is one of the recently developed meta-heuristic algorithms that is inspired by the Coulomb and Gauss’s laws of electrostatics in physics. In order to evaluate the efficiency of this algorithm, some numerical examples are utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the ECSS.

Parameter identification of Bouc-Wen model for MR fluid dampers using adaptive charged system search optimization

S. Talatahari 대한기계학회 2012 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.26 No.8

In this article, the charged system search (CSS) optimization method is improved to identify the parameters of a non-linear hysteretic Bouc-Wen differential model. The CSS is suitable for those optimization problems involving non-smooth or non-convex domains. Bouc-Wen is a well-established non-linear model which has been used to portray the hysteretic and high non-linear real behavior of numerous physical and mechanical systems. To improve the effectiveness and adaptability of the CSS algorithm, it is combined with suboptimization mechanism. The obtained results show that the adaptive CSS embodies great robustness and accuracy to be successfully employed in such highly non-linear identification problems.

Optimization of Large-Scale Frame Structures Using Fuzzy Adaptive Quantum Inspired Charged System Search

Siamak Talatahari,Mahdi Azizi,Mehdi Toloo,Milad Baghalzadeh Shishehgarkhaneh 한국강구조학회 2022 International Journal of Steel Structures Vol.22 No.3

In this paper, a metaheuristic-based design approach is developed in which the structural design optimization of large-scale steel frame structures is concerned. Although academics have introduced form-dominant methods, yet using artifi cial intelligence in structural design is one of the most critical challenges in recent years. However, the Charged System Search (CSS) is utilized as the primary optimization approach, which is improved by using the main principles of quantum mechanics and fuzzy logic systems. In the proposed Fuzzy Adaptive Quantum Inspired CSS algorithm, the position updating procedure of the standard algorithm is developed by implementing the center of potential energy presented in quantum mechanics into the general formulation of CSS to enhance the convergence capability of the algorithm. Simultaneously, a fuzzy logic-based parameter tuning process is also conducted to enhance the exploitation and exploration rates of the standard optimization algorithm. Two 10 and 60 story steel frame structures with 1026 and 8272 structural members, respectively, are utilized as design examples to determine the performance of the developed algorithm in dealing with complex optimization problems. The overall capability of the presented approach is compared with the Charged System Search and other metaheuristic optimization algorithms. The proposed enhanced algorithm can prepare better results than the other metaheuristics by considering the achieved results.

A New Hybrid Optimization Algorithm for Recognition of Hysteretic Non-linear Systems

S. Talatahari,N. Mohajer Rahbari,A. Kaveh 대한토목학회 2013 KSCE JOURNAL OF CIVIL ENGINEERING Vol.17 No.5

In this article, a new two-stage hybrid optimization method based on the Particle Swarm Optimization and the Big Bang-Big Crunch algorithm (BB-BC) is introduced for identification of highly non-linear systems. In this hybrid algorithm, the term of the center of mass from the BB-BC algorithm is incorporated into the standard particle swarm optimizer to markedly improve its searching abilities. In order to investigate the effectiveness of the newly formed optimization algorithm in identification of non-linear and hysteretic systems,it is utilized to optimally find the Bouc-Wen model’s parameters for a sample MR damper in which the damper’s force is related to its piston’s motion through a non-linear differential equation. The obtained results indicate that the proposed optimization method is highly robust and accurate and can be utilized successfully in such intricate non-linear identification problems.

A hybrid CSS and PSO algorithm for optimal design of structures

Kaveh, A.,Talatahari, S. Techno-Press 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.42 No.6

A new hybrid meta-heuristic optimization algorithm is presented for design of structures. The algorithm is based on the concepts of the charged system search (CSS) and the particle swarm optimization (PSO) algorithms. The CSS is inspired by the Coulomb and Gauss's laws of electrostatics in physics, the governing laws of motion from the Newtonian mechanics, and the PSO is based on the swarm intelligence and utilizes the information of the best fitness historically achieved by the particles (local best) and by the best among all the particles (global best). In the new hybrid algorithm, each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Three different types of structures are optimized as the numerical examples with the new algorithm. Comparison of the results of the hybrid algorithm with those of other meta-heuristic algorithms proves the robustness of the new algorithm.

Structural design with dynamic constraints using weighted chaos game optimization

Goodarzimehr Vahid,Talatahari Siamak,Shojaee Saeed,Hamzehei-Javaran Saleh,Sareh Pooya 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.6

The chaos game optimization (CGO) algorithm is a recently developed metaheuristic inspired by chaos theory and fractal configurations. In CGO, possible optimal solutions are defined as seeds and the searching process is performed using some simple equations. In this paper, weighted chaos game optimization (WCGO) is proposed and implemented to optimize engineering structures with dynamic constraints. In this method, an inertia weight coefficient based on the minimum and maximum values ​​of the objective function is introduced to create a better balance between exploration and exploitation during the searching process. By applying the inertia weight coefficient to the seeds, their positions can be controlled accurately. To evaluate the performance of WCGO, a wide range of mathematical benchmark functions, as well as several structural design optimization problems under dynamic constraints, are computationally investigated using the new algorithm. In order to demonstrate the efficiency and robustness of WCGO, its results have been compared with those obtained by some conventional methods from the literature. Additionally, a Friedman rank test is conducted to perform a statistical study on the performance of the considered algorithms. The findings indicate that WCGO performs better than its rivals in solving these structural optimization problems with dynamic constraints.

A hybrid CSS and PSO algorithm for optimal design of structures

A. Kaveh,S. Talatahari 국제구조공학회 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.42 No.6

A new hybrid meta-heuristic optimization algorithm is presented for design of structures. The algorithm is based on the concepts of the charged system search (CSS) and the particle swarm optimization (PSO) algorithms. The CSS is inspired by the Coulomb and Gauss’s laws of electrostatics in physics, the governing laws of motion from the Newtonian mechanics, and the PSO is based on the swarm intelligence and utilizes the information of the best fitness historically achieved by the particles (local best) and by the best among all the particles (global best). In the new hybrid algorithm, each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Three different types of structures are optimized as the numerical examples with the new algorithm. Comparison of the results of the hybrid algorithm with those of other metaheuristic algorithms proves the robustness of the new algorithm.

A Chaotic Imperialist Competitive Algorithm for Optimum Cost Design of Cantilever Retaining Walls

M. Pourbaba,S. Talatahari,R. Sheikholeslami 대한토목학회 2013 KSCE JOURNAL OF CIVIL ENGINEERING Vol.17 No.5

This paper develops a model to obtain the optimum cost of the cantilever retaining walls having different cases of backfill satisfying the stability criteria, according to the height and properties of earth that the wall is required to support. Chaotic Imperialist Competitive Algorithm (CICA) is utilized to find the economical sections as the output after minimizing the cost for sections adhering to provisions of ACI 318-05. The CICA, one of the recently developed meta-heuristic algorithms utilizes imperialism and imperialistic competition process combined with chaos theory as a source of inspiration. Cost design problem of cantilever retaining walls is tested using the new method and the results are compared to those of other algorithms. In addition, a detailed sensitivity analysis for selected design variables, parameters and related safety factors will be presented.

Optimum design of steel frames with semi-rigid connections using Big Bang-Big Crunch method

A. Rafiee,S. Talatahari,A. Hadidi 국제구조공학회 2013 Steel and Composite Structures, An International J Vol.14 No.5

The Big Bang-Big Crunch (BB-BC) optimization algorithm is developed for optimal design of non-linear steel frames with semi-rigid beam-to-column connections. The design algorithm obtains the minimum total cost which comprises total member plus connection costs by selecting suitable sections. Displacement and stress constraints together with the geometry constraints are imposed on the frame in the optimum design procedure. In addition, non-linear analyses considering the P-Δ effects of beam-column members are performed during the optimization process. Three design examples with various types of connections are presented and the results show the efficiency of using semi-rigid connection models in comparing to rigid connections. The obtained optimum semi-rigid frames are more economical solutions and lead to more realistic predictions of response and strength of the structure.

Optimum design of truss structures under frequency constraints using hybrid CSS-MBLS algorithm

Shahin Jalili,Siamak Talatahari 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.5

Optimum design of truss structures under frequency constraints is a complicated highly non-linear optimization problem with nonconvexsolution space. In this paper, a hybrid Charged System Search (CSS) algorithm with Migration-based Local Search (MBLS)is proposed for resolving this problem. The CSS algorithm as a developed metaheuristic optimization algorithm is inspired by thegoverning laws of electrostatics in physics and the governing laws of motion from the Newtonian mechanics. In the proposed hybridCSS-MBLS algorithm, the convergence speed of the standard CSS algorithm is enhanced by the MBLS mechanism. Numericalresults obtained from some design examples reveal the successfulness and effectiveness of the proposed algorithm in solving trussoptimum design problem under frequency constraints.