Optimal design of cyclically symmetric trusses with frequency constraints using cyclical parthenogenesis algorithm

2017 ◽  
Vol 21 (5) ◽  
pp. 739-755 ◽  
Author(s):  
A Kaveh ◽  
A Zolghadr
Keyword(s):  
Structural Analysis ◽  
Optimization Problems ◽  
Heuristic Method ◽  
Computational Time ◽  
Weight Optimization ◽  
Block Diagonalization ◽  
Cyclical Parthenogenesis ◽  
Frequency Constraints ◽  
Numerical Examples ◽  
Optimization Task

Special kinds of structures exhibit repetitive patterns that can be used in the process of structural analysis in order to decrease the required computational time. This is especially helpful when a structure should be analyzed numerous times as in the structural optimization problems. In this article, weight optimization of cyclically symmetric spatial trusses subjected to frequency constraints is performed utilizing such repetitive patterns. Large initial eigenproblems are first decomposed into smaller and less time-consuming problems using an efficient block diagonalization technique. A recently developed meta-heuristic method, cyclical parthenogenesis algorithm, is then utilized to perform the optimization task. Three numerical examples are optimized to illustrate the viability and efficiency of the proposed method.

An enhanced symbiotic organisms search algorithm for design optimization of trusses with frequency constraints

2021 ◽  
pp. 136943322110262
Author(s):  
Mohammad H Makiabadi ◽  
Mahmoud R Maheri
Keyword(s):  
Standard Deviation ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Metaheuristic Algorithms ◽  
Minimum Mass ◽  
Multiple Frequency ◽  
Frequency Constraints ◽  
Symbiotic Organisms Search ◽  
Symbiotic Organisms ◽  
Dynamic Frequency

An enhanced symbiotic organisms search (ESOS) algorithm is developed and presented. Modifications to the basic symbiotic organisms search algorithm are carried out in all three phases of the algorithm with the aim of balancing the exploitation and exploration capabilities of the algorithm. To verify validity and capability of the ESOS algorithm in solving general optimization problems, the CEC2014 set of 22 benchmark functions is first optimized and the results are compared with other metaheuristic algorithms. The ESOS algorithm is then used to optimize the sizing and shape of five benchmark trusses with multiple frequency constraints. The best (minimum) mass, mean mass, standard deviation of the mass, total number of function evaluations, and the values of frequency constraints are then compared with those of a number of other metaheuristic solutions available in the literature. It is shown that the proposed ESOS algorithm is generally more efficient in optimizing the shape and sizing of trusses with dynamic frequency constraints compared to other reported metaheuristic algorithms, including the basic symbiotic organisms search and its other recently proposed improved variants such as the improved symbiotic organisms search algorithm (ISOS) and modified symbiotic organisms search algorithm (MSOS).

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

1991 ◽  
Vol 2 (2-3) ◽  
pp. 175-182 ◽  
Author(s):  
D.T. Nguyen ◽  
O.O. Storaasli ◽  
E.A. Carmona ◽  
M. Al-Nasra ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Unconstrained Optimization ◽  
Optimization Problems ◽  
Unconstrained Optimization Problems ◽  
Non Linear

ON THE MODELLING AND SIMULATION OF HIGH PRESSURE PROCESSES AND INACTIVATION OF ENZYMES IN FOOD ENGINEERING

2009 ◽  
Vol 19 (12) ◽  
pp. 2203-2229 ◽  
Author(s):  
J. A. INFANTE ◽  
B. IVORRA ◽  
Á. M. RAMOS ◽  
J. M. REY
Keyword(s):  
High Pressure ◽  
Shelf Life ◽  
Food Processing ◽  
Modelling And Simulation ◽  
Computational Time ◽  
Thermal Treatments ◽  
Numerical Examples ◽  
Food Engineering

High Pressure (HP) Processing has turned out to be very effective in prolonging the shelf life of some food. This paper deals with the modelling and simulation of the effect of the combination of high pressure and thermal treatments on food processing, focusing on the inactivation of certain enzymes. The behavior and stability of the proposed models are checked by various numerical examples. Furthermore, various simplified versions of these models are presented and compared with each other in terms of accuracy and computational time. The models developed in this paper provide a useful tool to design suitable industrial equipments and optimize the processes.

scholarly journals Performance of the Modified Dolphin Monitoring Operator for Weight Optimization of Skeletal Structures

2018 ◽  
Author(s):  
Ali Kaveh ◽  
S.R. Hoseini Vaez ◽  
Pedram Hosseini
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Structural Optimization ◽  
Differential Evolution ◽  
Optimization Problems ◽  
Harmony Search ◽  
Average Weight ◽  
Weight Optimization ◽  
Swarm Optimization ◽  
Population Dispersion

In this study, the Modified Dolphin Monitoring (MDM) operator is used to enhance the performance of some metaheuristic algorithms. The MDM is a recently presented operator that controls the population dispersion in each iteration. Algorithms are selected from some well-established algorithms. Here, this operator is applied on Differential Evolution (DE), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Vibrating Particles System (VPS), Enhanced Vibrating Particles System (EVPS), Colliding Bodied Optimization (CBO) and Harmony Search (HS) and the performance of these algorithms are evaluated with and without this operator on three well-known structural optimization problems. The results show the performance of this operator on these algorithms for the best, the worst, average and average weight of the first quarter of answers.

scholarly journals Design & Weight Optimization of a Wheel Rim for Sport Utility Vehicle.

2018 ◽  
Vol 172 ◽  
pp. 03006
Author(s):  
Harish Panjagala ◽  
Balakrishna M ◽  
Shasikant Kushnoore ◽  
E L N Rohit Madhukar
Keyword(s):  
Structural Analysis ◽  
Point Of View ◽  
Weight Optimization ◽  
Strength Assessment ◽  
Suitable Material ◽  
The Road ◽  
Wheel Rim ◽  
Standard Values ◽  
Design Weight ◽  
Structural Point

Automobile have various parts which are important for good running of the vehicle. The most important safety components from a structural point of view are the road wheels. They are required to be lighter and more fascinating to the buyer all the time. This implies that it's important to perform a lot of accurate strength assessment on wheel styles. The wheel rim plays a major role in vehicle dynamics. This paper deals with the design and model of different wheel rims based on weight optimization and also structural analysis has been carried out. It has been compared with standard values by varying two different materials. In addition, from the obtained outputs of simulations and the weight optimization, we suggested Aluminium alloys as most suitable material for SUV. Model is created by using SOLIDWORKS software 2015 and structural analysis &; weight optimization is done by using ANSYS WORKBENCH 16.0.

scholarly journals A Unifying Representer Theorem for Inverse Problems and Machine Learning

2020 ◽  
Author(s):  
Michael Unser
Keyword(s):  
Machine Learning ◽  
Banach Spaces ◽  
Tikhonov Regularization ◽  
Optimization Problems ◽  
Broad Class ◽  
Training Problem ◽  
Optimization Task ◽  
Machine Leaning ◽  
Sparse Solutions ◽  
Standard Strategy

Abstract Regularization addresses the ill-posedness of the training problem in machine learning or the reconstruction of a signal from a limited number of measurements. The method is applicable whenever the problem is formulated as an optimization task. The standard strategy consists in augmenting the original cost functional by an energy that penalizes solutions with undesirable behavior. The effect of regularization is very well understood when the penalty involves a Hilbertian norm. Another popular configuration is the use of an $$\ell _1$$ ℓ 1 -norm (or some variant thereof) that favors sparse solutions. In this paper, we propose a higher-level formulation of regularization within the context of Banach spaces. We present a general representer theorem that characterizes the solutions of a remarkably broad class of optimization problems. We then use our theorem to retrieve a number of known results in the literature such as the celebrated representer theorem of machine leaning for RKHS, Tikhonov regularization, representer theorems for sparsity promoting functionals, the recovery of spikes, as well as a few new ones.

Three-Dimensional Paddle Shift Modeling for IC Packaging

2004 ◽  
Vol 127 (3) ◽  
pp. 324-334 ◽  
Author(s):  
Chien-Chang Pei ◽  
Sheng-Jye Hwang
Keyword(s):  
Structural Analysis ◽  
Integrated Circuits ◽  
Three Dimensional ◽  
Void Formation ◽  
Model Performance ◽  
Computational Time ◽  
Pressure Loading ◽  
Filling Process ◽  
Molding Process ◽  
Incomplete Filling

The plastic packaging process for integrated circuits is subject to several fabrication defects. For packages containing leadframes, three major defects may occur in the molding process alone, namely, incomplete filling and void formation, wire sweep, and paddle shift. Paddle shift is the deflection of the leadframe pad and die. Excessive paddle shift reduces the encapsulation protection for the components and may result in failures due to excessive wire sweep. Computer-aided analysis is one of the tools that could be used to simulate and predict the occurrence of such molding-process-induced defects, even prior to the commencement of mass production of a component. This paper presents a methodology for computational modeling and prediction of paddle shift during the molding process. The methodology is based on modeling the flow of the polymer melt around the leadframe and paddle during the filling process, and extracting the pressure loading induced by the flow on the paddle. The pressure loading at different times during the filling process is then supplied to a three-dimensional, static, structural analysis module to determine the corresponding paddle deflections at those times. The paper outlines the procedures used to define the relevant geometries and to generate the meshes in the “fluid” and “structural” subdomains, and to ensure the compatibility of these meshes for the transfer of pressure loadings. Results are shown for a full paddle shift simulation. The effect on the overall model performance of different element types for the mold-filling analysis and the structural analysis is also investigated and discussed. In order to obtain more accurate results and in a shorter computational time for the combined (fluid and structural) paddle shift analysis, it was found that higher-order elements, such as hexahedra or prisms, are more suitable than tetrahedra.

scholarly journals Ions motion optimization algorithm for multiobjective optimization problems

2021 ◽  
pp. 93-110 ◽  
Author(s):  
Hitarth Buch ◽  
Indrajit Trivedi
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Computational Time ◽  
Selection Strategy ◽  
Pareto Optimum ◽  
Optimal Solutions ◽  
Good Convergence ◽  
Motion Optimization ◽  
Multiobjective Approach ◽  
Benchmark Test Functions

This paper offers a novel multiobjective approach – Multiobjective Ions Motion Optimization (MOIMO) algorithm stimulated by the movements of ions in nature. The main inspiration behind this approach is the force of attraction and repulsion between anions and cations. A storage and leader selection strategy is combined with the single objective Ions Motion Optimization (IMO) approach to estimate the Pareto optimum front for multiobjective optimization. The proposed method is applied to 18 different benchmark test functions to confirm its efficiency in finding optimal solutions. The outcomes are compared with three novel and well-accepted techniques in the literature using five performance parameters quantitatively and obtained Pareto fronts qualitatively. The comparison proves that MOIMO can approximate Pareto optimal solutions with good convergence and coverage with minimum computational time.

scholarly journals An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems

2022 ◽  
Vol 19 (1) ◽  
pp. 473-512
Author(s):  
Rong Zheng ◽  
◽  
Heming Jia ◽  
Laith Abualigah ◽  
Qingxin Liu ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
Heuristic Method ◽  
Population Diversity ◽  
Test Functions ◽  
Design Problems ◽  
Local Optima ◽  
Switching Mechanism ◽  
Engineering Design Problems

<abstract> <p>Arithmetic optimization algorithm (AOA) is a newly proposed meta-heuristic method which is inspired by the arithmetic operators in mathematics. However, the AOA has the weaknesses of insufficient exploration capability and is likely to fall into local optima. To improve the searching quality of original AOA, this paper presents an improved AOA (IAOA) integrated with proposed forced switching mechanism (FSM). The enhanced algorithm uses the random math optimizer probability (<italic>RMOP</italic>) to increase the population diversity for better global search. And then the forced switching mechanism is introduced into the AOA to help the search agents jump out of the local optima. When the search agents cannot find better positions within a certain number of iterations, the proposed FSM will make them conduct the exploratory behavior. Thus the cases of being trapped into local optima can be avoided effectively. The proposed IAOA is extensively tested by twenty-three classical benchmark functions and ten CEC2020 test functions and compared with the AOA and other well-known optimization algorithms. The experimental results show that the proposed algorithm is superior to other comparative algorithms on most of the test functions. Furthermore, the test results of two training problems of multi-layer perceptron (MLP) and three classical engineering design problems also indicate that the proposed IAOA is highly effective when dealing with real-world problems.</p> </abstract>

scholarly journals METHODS OF FORMULATING AND SOLVING OPTIMIZATION PROBLEMS OF CUTTING LOGS OF LARGE SIZE BY BAR-SAWING METHOD WITH CUTTING OUT ONE BAR AND FIVE PAIRS OF SIDE EDGING BOARDS WITH SUBSEQUENT SAWING LUMBER FOR EDGED BOARDS

2017 ◽  
Vol 7 (1) ◽  
pp. 137-150
Author(s):  
Агапов ◽  
Aleksandr Agapov
Keyword(s):  
Mathematical Model ◽  
Objective Function ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Target Function ◽  
Cross Sectional ◽  
Optimization Task ◽  
Cutting Out ◽  
The Mathematical Model ◽  
The Relationship

For the first time the mathematical model of task optimization for this scheme of cutting logs, including the objective function and six equations of connection. The article discusses Pythagorean area of the logs. Therefore, the target function is represented as the sum of the cross-sectional areas of edging boards. Equation of the relationship represents the relationship of the diameter of the logs in the vertex end with the size of the resulting edging boards. This relationship is described through the use of the Pythagorean Theorem. Such a representation of the mathematical model of optimization task is considered a classic one. However, the solution of this mathematical model by the classic method is proved to be problematic. For the solution of the mathematical model we used the method of Lagrange multipliers. Solution algorithm to determine the optimal dimensions of the beams and side edging boards taking into account the width of cut is suggested. Using a numerical method, optimal dimensions of the beams and planks are determined, in which the objective function takes the maximum value. It turned out that with the increase of the width of the cut, thickness of the beam increases and the dimensions of the side edging boards reduce. Dimensions of the extreme side planks to increase the width of cut is reduced to a greater extent than the side boards, which are located closer to the center of the log. The algorithm for solving the optimization problem is recommended to use for calculation and preparation of sawing schedule in the design and operation of sawmill lines for timber production. When using the proposed algorithm for solving the optimization problem the output of lumber can be increased to 3-5 %.

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