scholarly journals Minimizing the Weight of Cantilever Beam via Metaheuristic Methods by Using Different Population-Iteration Combinations

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Cantilever Beam ◽  
Optimization Problem ◽  
Beam Model ◽  
Hollow Section ◽  
Bee Colony ◽  
Metaheuristic Methods ◽  
Long Time ◽  
Parameter Values ◽  
Structural Optimization Problem ◽  
Minimum Objective Function

Since a long time, metaheuristic algorithms are benefited to detect the best results for any optimization problem. Furthermore, these methods are used to prevent of time, effort and cost losses, while they are performing the optimization process. Hence, in this study, a cantilever beam model, which is one of the structural optimization problem from civil engineering area, was handled with the aim of minimization of the total weight by find the optimum section values consisting of hollow section depths and widths. For this reason, three different methods including the algorithms that artificial bee colony (ABC), bat (BA), and a modified bat (MBA) combining of BA with Lévy flight, were operated. Additionally, several applications previously carried out for this model, were presented in order to compare of optimization results (minimum objective function with optimum design variable values), and success of proposed algorithm was showed with statistical results and optimization parameter values.

Study on Optimal Method for PID Parameter Based on Artificial Bee Colony Algorithm

2014 ◽  
Vol 624 ◽  
pp. 454-459 ◽  
Author(s):  
Guang Chun Li ◽  
Ping Yan ◽  
Sui Er Wang
Keyword(s):  
Control System ◽  
Parameter Optimization ◽  
Artificial Bee Colony Algorithm ◽  
Optimization Problem ◽  
Artificial Bee Colony ◽  
System Research ◽  
Optimal Method ◽  
Bee Colony ◽  
Optimization Control ◽  
Long Time

The PID parameter optimization has been a hot topic of control system research. Artificial bee colony algorithm is used to optimize the PID parameters of control system, and gives the PID parameter optimization process of the traditional artificial bee colony algorithm. Aiming at the optimization problem of long time, the improved artificial bee colony algorithm was put forward. The simulation results show that the improved artificial bee colony algorithm can significantly shorten the time of PID parameter optimization, control and better optimization accuracy.

scholarly journals Least-thickness symmetric circular masonry arch of maximum horizontal thrust

2021 ◽  
Author(s):  
Giuseppe Cocchetti ◽  
Egidio Rizzi
Keyword(s):  
Optimization Problem ◽  
Research Work ◽  
Complementary Information ◽  
Masonry Arch ◽  
Collapse Mode ◽  
Hinge Position ◽  
Explicit Representations ◽  
Horizontal Thrust ◽  
Structural Optimization Problem ◽  
Typical Solution

AbstractThis analytical note shall provide a contribution to the understanding of general principles in the Mechanics of (symmetric circular) masonry arches. Within a mainstream of previous research work by the authors (and competent framing in the dedicated literature), devoted to investigate the classical structural optimization problem leading to the least-thickness condition under self-weight (“Couplet-Heyman problem”), and the relevant characteristics of the purely rotational five-hinge collapse mode, new and complementary information is here analytically derived. Peculiar extremal conditions are explicitly inspected, as those leading to the maximum intrinsic non-dimensional horizontal thrust and to the foremost wide angular inner-hinge position from the crown, both occurring for specific instances of over-complete (horseshoe) arches. The whole is obtained, and confronted, for three typical solution cases, i.e., Heyman, “CCR” and Milankovitch instances, all together, by full closed-form explicit representations, and elucidated by relevant illustrations.

USING AN IMPROVED BEE MEMORY DIFFERENTIAL EVOLUTION ALGORITHM FOR PARAMETER ESTIMATION TO SIMULATE BIOCHEMICAL PATHWAYS

2014 ◽  
Vol 22 (01) ◽  
pp. 101-121 ◽  
Author(s):  
CHUII KHIM CHONG ◽  
MOHD SABERI MOHAMAD ◽  
SAFAAI DERIS ◽  
MOHD SHAHIR SHAMSIR ◽  
LIAN EN CHAI ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Estimation Algorithm ◽  
Convergence Time ◽  
Unknown Parameters ◽  
Estimation Algorithms ◽  
Bee Colony ◽  
De Algorithm ◽  
Cell Cycle Pathway ◽  
Parameter Values

When analyzing a metabolic pathway in a mathematical model, it is important that the essential parameters are estimated correctly. However, this process often faces few problems like when the number of unknown parameters increase, trapping of data in the local minima, repeated exposure to bad results during the search process and occurrence of noisy data. Thus, this paper intends to present an improved bee memory differential evolution (IBMDE) algorithm to solve the mentioned problems. This is a hybrid algorithm that combines the differential evolution (DE) algorithm, the Kalman filter, artificial bee colony (ABC) algorithm, and a memory feature. The aspartate and threonine biosynthesis pathway, and cell cycle pathway are the metabolic pathways used in this paper. For three production simulation pathways, the IBMDE managed to robustly produce the estimated optimal kinetic parameter values with significantly reduced errors. Besides, it also demonstrated faster convergence time compared to the Nelder–Mead (NM), simulated annealing (SA), the genetic algorithm (GA) and DE, respectively. Most importantly, the kinetic parameters that were generated by the IBMDE have improved the production rates of desired metabolites better than other estimation algorithms. Meanwhile, the results proved that the IBMDE is a reliable estimation algorithm.

An Approach to Approximate the Full Strain Field of Turbofan Blades During Operation

2018 ◽  
Author(s):  
Gen Fu ◽  
Alexandrina Untaroiu ◽  
Walter O’Brien
Keyword(s):  
Numerical Model ◽  
Cantilever Beam ◽  
Strain Field ◽  
Measured Data ◽  
Mode Shapes ◽  
Beam Model ◽  
Reference Solution ◽  
Full Field ◽  
Field Response ◽  
Critical Locations

The measurement of the aeromechanical response of the fan blades is important to quantifying their integrity. The accurate knowledge of the response at critical locations of the structure is crucial when assessing the structural condition. A reliable and low cost measuring technique is necessary. Currently, sensors can only provide the measured data at several discrete points. A significant number of sensors may be required to fully characterize the aeromechanical response of the blades. However, the amount of instrumentation that can be placed on the structure is limited due to data acquisition system limitations, instrumentation accessibility, and the effect of the instrumentation on the measured response. From a practical stand point, it is not possible to place sensors at all the critical locations for different excitations. Therefore, development of an approach that derives the full strain field response based on a limited set of measured data is required. In this study, the traditional model reduction method is used to expand the full strain field response of the structure by using a set of discrete measured data. Two computational models are developed and used to verify the expansion approach. The solution of the numerical model is chosen as the reference solution. In addition, the numerical model also provides the mode shapes of the structure. In the expansion approach, this information is used to develop the algorithm. First, a cantilever beam model is created. The influences of the sensor location, number of sensors and the number of modes included are analyzed using this cantilever beam model. The expanded full field response data is compared with the reference solution to evaluate the expansion procedure. The rotor 67 blade model is then used to test the expansion method. The results show that the expanded full field data is in good agreement with the calculated data. The expansion algorithm can be used for the full field strain by using the limited sets of strain data.

Study on Flexibility of Intracranial Vascular Stents Based on the Finite Element Method

2018 ◽  
Vol 35 (4) ◽  
pp. 465-474 ◽  
Author(s):  
L. Liu ◽  
H. Jiang ◽  
Y. Dong ◽  
L. Quan ◽  
Y. Tong
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Cantilever Beam ◽  
Beam Model ◽  
The Finite Element Method ◽  
Simply Supported Beam ◽  
Bending Deformation ◽  
Vascular Stents ◽  
Simply Supported ◽  
Loading Method

ABSTRACTFlexibility is a particularly important biomechanical property for intracranial vascular stents. To study the flexibility of stent, the following work was carried out by using the finite element method: Four mechanical models were adopted to simulate the bending deformation of stents, and comparative studies were conducted about the distinction between cantilever beam and simply supported beam, as well as the distinction between moment-loading method and displacement-loading method. A complete process as implanting a stent including compressing, expanding and bending was also simulated, for analyzing the effects of compressing and expanding deformation on stent flexibility. At the same time, the effects of the arrangement and the number of bridges on stent flexibility were researched. The results show that: 1. A same flexibility index was obtained from cantilever beam model and simply supported beam model; displacement-loading method is better than moment-loading for simulating the bending deformation of stents. 2. The flexibility of stent with compressing and expanding deformation is lower than that in the initial form. 3. Crossly arranging the neighboring bridges in axial direction, can effectively improve the stent flexibility and reduce the flexibility difference in various bending directions; the bridge number, has proportional non-linear correlation with the stent rigidity as well as the maximum moment required for bending the stent.

scholarly journals A Reactive Population Approach on the Dolphin Echolocation Algorithm for Solving Cell Manufacturing Systems

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1389
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Rodrigo Olivares ◽  
César Carrasco ◽  
Eduardo Rodriguez-Tello ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Optimization Problem ◽  
Local Optimum ◽  
Cell Manufacturing ◽  
Intelligence Algorithm ◽  
Autonomous Search ◽  
Parameter Values ◽  
Swarm Intelligence Algorithm

In this paper, we integrate the autonomous search paradigm on a swarm intelligence algorithm in order to incorporate the auto-adjust capability on parameter values during the run. We propose an independent procedure that begins to work when it detects a stagnation in a local optimum, and it can be applied to any population-based algorithms. For that, we employ the autonomous search technique which allows solvers to automatically re-configure its solving parameters for enhancing the process when poor performances are detected. This feature is dramatically crucial when swarm intelligence methods are developed and tested. Finding the best parameter values that generate the best results is known as an optimization problem itself. For that, we evaluate the behavior of the population size to autonomously be adapted and controlled during the solving time according to the requirements of the problem. The proposal is testing on the dolphin echolocation algorithm which is a recent swarm intelligence algorithm based on the dolphin feature to navigate underwater and identify prey. As an optimization problem to solve, we test a machine-part cell formation problem which is a widely used technique for improving production flexibility, efficiency, and cost reduction in the manufacturing industry decomposing a manufacturing plant in a set of clusters called cells. The goal is to design a cell layout in such a way that the need for moving parts from one cell to another is minimized. Using statistical non-parametric tests, we demonstrate that the proposed approach efficiently solves 160 well-known cell manufacturing instances outperforming the classic optimization algorithm as well as other approaches reported in the literature, while keeping excellent robustness levels.

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