فهرست مقالات Simulated Annealing (SA)

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  1 - Using design of experiments approach and simulated annealing algorithm for modeling and Optimization of EDM process parameters
  Masoud Azadi Moghaddam Farhad Kolahan Meysam Beytolamani
  The main objectives of this research are, therefore, to assess the effects of process parameters and to determine their optimal levels machining of Inconel 718 super alloy. gap voltage, current, time of machining and duty factor are tuning parameters considered to be st چکیده کامل

  The main objectives of this research are, therefore, to assess the effects of process parameters and to determine their optimal levels machining of Inconel 718 super alloy. gap voltage, current, time of machining and duty factor are tuning parameters considered to be study as process input parameters. Furthermore, two important process output characteristic, have been evaluated in this research are material removal rate (MRR) and surface roughness (SR). Determination of a combination of process parameters to minimize SR and maximize MRR is the objective of this study. In order to gather required experimental data, design of experiments (DOE) approach, has been used. Then, statistical analyses and validation experiments have been carried out to select the best and the most fitted regression models. In the last section of this research, simulated annealing (SA) algorithm has been employed for optimization of the EDM process performance characteristics. A set of verification tests is also performed to confirm the accuracy of the proposed optimization procedure in determining the optimal levels of machining parameters. The results indicate that the proposed modeling technique and SA algorithm are quite efficient in modeling and optimization of EDM process parameters. پرونده مقاله
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  2 - Simultaneously Modeling and Optimization of Heat Affected Zone and Tensile Strength in GTAW Process Using Simulated Annealing Algorithm
  Meysam Beytolamani Masoud Azadi Moghaddam Farhad Kolahan
  In the present study, a technique has been addressed in order to model and optimize gas tungsten arc welding (GTAW) process which is one of the mostly used welding processes based on the high quality fabrication acquired. The effects of GTAW process variables on the joi چکیده کامل

  In the present study, a technique has been addressed in order to model and optimize gas tungsten arc welding (GTAW) process which is one of the mostly used welding processes based on the high quality fabrication acquired. The effects of GTAW process variables on the joint quality of AISI304 stainless steel thin sheets (0.5 mm) have been investigated. The required data for modeling and optimization purposes has been gathered using Taguchi design of experiments (DOE) technique. Next, based on the acquired data, the modeling procedure has been performed using regression functions for two outputs; namely, heat affected zone (HAZ) width and ultimate tensile stress (UTS). Then, analysis of variance (ANOVA) has been performed in order to select the most fitted proposed models for single-objective and multi-criteria optimization of the process in such a way that UTS is maximized and HAZ width minimized using simulated annealing (SA) algorithm. Frequency, welding speed, base current and welding current are the most influential variables affecting the UTS at 22%, 21%, 20% and 17% respectively. Similarly, base current, welding current, frequency and welding speed affect the HAZ at 28%, 20%, 16%, and 15% respectively. Based on the results considering the lowest values for current results in the smallest amount of HAZ. By the same token in order to acquire the largest amount of UTSs the highest values of current must be considered. Setting welding and base current, frequency, speed, and debi at 42 and 5 apms, 46 Hz, 0.4495 m/min, and 5 lit/min respectively resulted the optimized HAZ and UTS simultaneously. The proper performance of the proposed optimization method has been proved through comparison between computational results and experimental data with less than 6% error. پرونده مقاله
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  3 - Cuckoo Optimization Algorithm in Cutting Conditions During Machining
  Ahmad Esfandiari
  Optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. In recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. The Cuc چکیده کامل

  Optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. In recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. The Cuckoo Optimization Algorithm (COA) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and their lifestyle. In this paper, COA, Simulated Annealing (SA), Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA) are first applied to five test functions and the performance of these algorithms is compared. These algorithms are then used to optimize the cutting conditions. The results showed that COA has more capabilities such as accuracy, faster convergence and better global optimum achievement than others. پرونده مقاله
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  4 - A New Optimal Correlation for Behavior factor of EBFs under Near-fault Earthquakes using Artificial Intelligence Models
  Seyed Abdonnabi Razavi Navid Siahpolo
  10.1007/ijase.2022.698628
  Behavior factor of the structures is a coefficient that includes the inelastic performance of the structure and indicates the hidden resistance of the structure in the inelastic stage. In most seismic codes, this coefficient is merely dependent on the type of lateral re چکیده کامل

  Behavior factor of the structures is a coefficient that includes the inelastic performance of the structure and indicates the hidden resistance of the structure in the inelastic stage. In most seismic codes, this coefficient is merely dependent on the type of lateral resistance system and is introduced with a fixed number. However, there is a relationship between the behavior factor, ductility (performance level), structural geometric properties, and type of earthquake (near and far). In this paper, a new optimal correlation is attempted to predict the behavior factor (q) of EBF steel frames, under near-fault earthquakes, using Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms. For this purpose, a databank consists of 12960 data created. To establishing different geometrical properties of models, 3-,6-, 9-, 12-, 15, 20- stories steel EBF frames considered with 3 different types of link beam, 3 different types of column stiffness and 3 different types of brace slenderness. Using nonlinear time history under 20 near-fault earthquake, all models analyzed to reach 4 different performance level. data were used as training data of the Artificial Intelligence Models. Results shows the high accuracy of proposed correlation, established by PSO algorithm. The results of the correlation between the studied algorithms show more accuracy in the relations produced than the previous algorithms and confirm the significance of the governing relations. پرونده مقاله