Ali Hadidi

Bio: Ali Hadidi is an academic researcher from University of Tabriz. The author has contributed to research in topics: Damper & Optimal design. The author has an hindex of 7, co-authored 20 publications receiving 225 citations.

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

Abstract: 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- 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.

Harmony search based, improved Particle Swarm Optimizer for minimum cost design of semi-rigid steel frames

Abstract: This paper proposes a Particle Swarm Optimization (PSO) algorithm, which is improved by making use of the Harmony Search (HS) approach and called HS-PSO algorithm. A computer code is developed for optimal sizing design of non-linear steel frames with various semi-rigid and rigid beam-tocolumn connections based on the HS-PSO algorithm. The developed code selects suitable sections for beams and columns, from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange W-shapes, such that the minimum total cost, which comprises total member plus connection costs, is obtained. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the optimal design procedure. The nonlinear moment-rotation behavior of connections is modeled using the Frye-Morris polynomial model. Moreover, the P-A effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark design examples with several types of connections are presented and the results are compared with those of standard PSO and of other researches as well. The comparison shows that the proposed HS-PSO algorithm performs better both than the PSO and the Big Bang-Big Crunch (BB-BC) methods.

A new hybrid algorithm for simultaneous size and semi-rigid connection type optimization of steel frames

Abstract: A hybrid algorithm based on Harmony Search (HS) and Big Bang-Big Crunch (BB-BC) optimization methods is proposed for optimal design of semi-rigid steel frames. The algorithm selects suitable sections for beams and columns and assigns suitable semi-rigid connection types for beam-to-column connections, such that the total member plus connection cost of the frame, is minimized. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the design procedure. The nonlinear moment-rotation behavior of connections and P-Δ effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark steel frames are designed and the results are compared with those of standard BB-BC and of other studies. The comparisons demonstrate that proposed algorithm performs better than standard BB-BC and HS methods in all examples and that the total cost of a frame can be reduced through suitable selection of its beam-to-column connection types.

Charged system search for optimal design of frame structures

Abstract: The charged system search (CSS) algorithm is utilized for design of frame structures. The algorithm is inspired by the laws in physics. The CSS utilizes a number of charged particles which influence each other based on their fitness values and their separation distances considering the governing law of Coulomb. A comparison between the characteristics of the CSS algorithm and other well-known meta-heuristics is performed to indicate their similarities and differences. Some benchmark frame examples are optimized with the CSS algorithm. Comparison of the results of CSS with some other meta-heuristic algorithms shows the robustness of the new algorithm.

A new hybrid particle swarm and simulated annealing stochastic optimization method

Abstract: Display Omitted Development of a new hybrid PSO-SA optimization method.Numerical validation of the proposed method using a number of benchmark functions.Using three criteria for comparative work.Finding near optimum parameters of the proposed method.Application of the proposed algorithm in two engineering problems. A novel hybrid particle swarm and simulated annealing stochastic optimization method is proposed. The proposed hybrid method uses both PSO and SA in sequence and integrates the merits of good exploration capability of PSO and good local search properties of SA. Numerical simulation has been performed for selection of near optimum parameters of the method. The performance of this hybrid optimization technique was evaluated by comparing optimization results of thirty benchmark functions of different dimensions with those obtained by other numerical methods considering three criteria. These criteria were stability, average trial function evaluations for successful runs and the total average trial function evaluations considering both successful and failed runs. Design of laminated composite materials with required effective stiffness properties and minimum weight design of a three-bar truss are addressed as typical applications of the proposed algorithm in various types of optimization problems. In general, the proposed hybrid PSO-SA algorithm demonstrates improved performance in solution of these problems compared to other evolutionary methods The results of this research show that the proposed algorithm can reliably and effectively be used for various optimization problems.