MATLAB Genetic Algorithm Research Articles

FEA of friction stir welding of AA1100 and parametric optimization using genetic algorithm

3D uncoupled thermo-mechanical analysis of friction stir welding (FSW) of aluminum alloy AA1100 was carried out using FEM. The heat generated in the FSW process is applied via DFLUX subroutine of ABAQUS. Simulations with different process parameters such as welding speed and rotational speed were performed for the estimation of temperature generated during the FSW process. Thermal analysis’s output is applied as thermal loads during mechanical analysis. Subsequently, residual stress developed during the FSW process was found out. Residual stresses were measured along the selected path, which included node to node stress variations in longitudinal directions. Maximum temperature appears to occur at the center of the weld pool and decreases away from the weld line towards the base metal. The numerical and experimental results were successfully validated with error in the range of 0.5 - 6%. Then, a semi-analytical equation for temperature distribution considering moving point heat source is proposed to carry out single objective unconstrained optimization of process parameters (welding speed and rotational speed). Finally, optimization was carried out to estimate the maximum temperature generated during the FSW process using a genetic algorithm in MATLAB.

Analysis and Research on the Automatic Control Systems of Oil–Water Baffles in Horizontal Three-Phase Separators

The three-phase separator is one of the most important pieces of equipment in the combined station of the oilfield. The control level of the oil–water interface directly affects the energy consumption of the subsequent production of the combined station and the effect of oil, gas and water separation. In order to avoid these situations, the Siemens PLC control system, configuration software WinCC and MATLAB were used. The OPC technology is used to connect communication between WinCC and MATLAB, and the genetic algorithm in MATLAB is used to obtain the optimal separation height of the oil–water interface under the produced liquid in different periods. Subsequently, through the Siemens PLC system and WinCC configuration software, the automatic control of the three-phase separator is achieved, and finally the water content of crude oil is significantly reduced. The system provides a visual interface function. In the future, it will also provide an effective simulation platform for the theoretical research and design of an automatic control system of an oilfield combined station.

Fast designing approach for planar graphene filtering leaky-wave antennas

In this paper a new fast designing approach for planar filtering leaky-wave antennas, is proposed. The introduced designing procedure, is based on the method of Moments, and fully implemented in MATLAB. In addition to novelty, the introduced designing procedure, can add any desired filtering property to a wideband LWA without using additional circuits, and design LWAs without periodical changes; so it is powerful than the Floquet method. Furthermore, the impedance matching of leaky-wave antenna with photomixer is another challenging issue that has been addressed in this article, for the first time. The proposed antenna is a slotted microstrip with a non-periodic pattern, unlike all known LWAs. Graphene is used for the micro ribbon, instead of the electric conductor, because of its wonderful properties. The suitable pattern of slots on the graphene microstrip, is obtained using optimization performed by MATLAB Genetic algorithm tool, to have an appropriate radiation, and filtering properties simultaneously. The usefulness and performance of the presented designing approach, is verified in one example. It has been illustrated that it has additional features, in comparison with one of the new similar antennas. Moreover, the result obtained by introduced strategy is compared with that obtained by CST for validation.

Optimal design and control of three simplified sargent four-product dividing-wall columns

Sargent columns have been shown to reduce energy consumption significantly for chemical separations with four product streams. However, the number of vapor splits needed to operate the system poses operational concerns. As a result, simplified configurations have been investigated to reduce vapor splits. This study aims to examine the economic design followed by dynamic performance analysis of three simplified alternative configurations, i.e., s-2-3-4, 2-2-4, and 2-3-3, to the Sargent column, for the separation of a Benzene-Toluene-Xylene (BTX) mixture. The designs were obtained through rigorous simulations in AspenPlus, linked to an optimization code using genetic algorithms in Matlab. The optimization problem considers the total annual cost (TAC) minimization. Optimal designs of the simplified alternatives are economically attractive, with 26 to 33% savings in TAC over the conventional sequence. The dynamic performance of simplified DWCs was studied through temperature-only PID control schemes in a multi-loop framework. The results show that simplified dividing wall columns (DWCs) provide suitable performance without considering vapor splits as manipulated inputs. Small variations from nominal product specifications (<0.25 mole%) were observed after the throughput and composition feed disturbances were imposed. Thus, this work demonstrates that the studied simplified DWC alternatives are attractive options for industrial implementation.

A Genetic Algorithm-Based Model for Inventory Control in Intermittent Demands

Demand forecasting is a difficult field of study for intermittent demands. Spare parts demand structures also have an intermittent demand structure. Therefore, for companies operating in this field, this situation causes various problems (holding cost or cost of lost sale). Intermittent demands are inherently difficult to predict. Demands with a smooth structure provide a more suitable working environment for businesses. Because the more accurately the relevant demand is forecasted, the more smoothly the works that depend on demand forecasting are carried on. In this study, a randomly generated demand series with intermittent demand structure is examined. The estimation difficulty of intermittent demand is illustrated by an estimation made in Matlab. In order to avoid this difficulty, the costs were tried to be minimized by determining the inventory levels. An inventory model is proposed that determines stock levels using intermittent demands and calculates average profit by calculating costs. The related model was solved with Genetic Algorithm in Matlab and the results were recorded.

Analysis of the Comprehensive Evaluation Model of Enterprise Technological Innovation Ability Based on Improved Genetic Algorithm

In an environment where technology is developing rapidly, product life cycles are constantly shortening, competition is increasing, and innovation resources are easily acquired by other competitors, it is particularly important for companies to successfully implement technological innovation. It is of great significance for companies to find the weak links of their technological innovation and prioritize improvement and enhancement of their technological innovation capabilities. As the main body of the agricultural machinery industry, private agricultural machinery enterprises are playing an increasingly important role. A correct understanding of the technological innovation activities of private agricultural machinery enterprises and the establishment of a reasonable evaluation index system for technological innovation capabilities are of great significance to the technological innovation management of private agricultural machinery enterprises. In accordance with the theory of technological innovation and the characteristics of private agricultural machinery enterprises, a technical innovation evaluation index system for private agricultural machinery enterprises has been established. The indicator system starts from the concept of private agricultural machinery enterprises, analyzes the status quo and development trend of the agricultural machinery industry, and takes private agricultural machinery enterprises in Heilongjiang Province as the research object. It summarizes the status quo and characteristics of technological innovation of private agricultural machinery enterprises and then establishes the private agricultural machinery enterprises. The system starts from the aspects of innovation resource input, innovation output, technology density, innovation effect, market realization, and innovation tendency, and selects 16 specific evaluation indicators. According to the established capability, projection pursuit is adopted. The method combined with the genetic algorithm and the genetic algorithm in MATLAB and the direct search toolbox were employed to comprehensively charge the capabilities of the five sample enterprises, and the evaluation results were objective and credible.

Optimizing the Aerothermomechanical Behavior of Sandwich Panels Using Genetic Algorithm

A multi-objective optimization of a sandwich structure is presented to maximize the fundamental frequency and the critical buckling temperature while minimizing the cost of the laminate, alongside with keeping the weight lower than a preset value. The sandwich structure was chosen to be made of a high-stiffness, relatively expensive material (carbon/epoxy), and a low-stiffness, relatively low- cost material for the core (glass/epoxy). The governing equations are derived using the principle of virtual work, based on the first-order shear deformation plate theory. MATLAB Genetic Algorithm toolbox is used to find the optimum stacking sequence and ply thicknesses to achieve the optimal solution. The ground structure was used to set the initial ply stacking sequence and then the algorithm assumes the existence or absence of each ply and their thicknesses. The optimum buckling temperature and natural frequency values are introduced for different aerodynamic pressure values and under simply supported boundary condition.

Genetic algorithm based design optimization of crashworthy honeycomb sandwiched panels of AA7075-T651 aluminium alloy for aerospace applications

Crashworthiness studies, for decades have been an area of tremendous interest in aerospace and automotive sectors, as ensuring the safety of the occupants in the vehicle is a primary goal. Honeycomb sandwich panels are generally used for building floor, ceiling and other important fuselage parts in a commercial airliner to make the structures shock-resistant. In this work, optimization of the design of crashworthy sandwiched honeycomb structure was carried out using a non-dominated sorting genetic algorithm (NSGA) . The stated algorithm had actively monitored the variation of the geometric parameters. To study the shape effect of the cells which absorb impact energy, three cellular shapes namely hex-grid, ortho-grid and iso-grid structures were considered for analyzing their deformation behavior under impact loading. A multi objective function in the genetic algorithm was implemented in MATLAB, where the objectives were to minimize weight and to maximize the absorbed impact energy while constraining the maximum transmitted force and displacement due to crushing. Sandwiched aluminum (AA7075-T651) honeycomb structures were modeled in ABAQUS using python scripts , with the number of core cells and the wall thickness of each core cell being optimized through genetic algorithm in MATLAB using an interactive mechanism. Significant improvements were observed in terms of reduction of weight and increase in the ability to absorb the specific energy during crushing in the sandwiched panels after 450 iterations of optimization cycles. A novel methodology in the domain of crash analysis of aerostructures was established with design optimization of honeycomb sandwiched panels.

Multi-objective optimization and analysis for laser beam cutting of stainless steel (SS304) using hybrid statistical tools GA-RSM

A laser beam machine is a non-traditional manufacturing technique that uses thermal energy to cut nearly all types of materials. The quality of laser cutting is significantly affected by process parameters. The purpose of this study is to use a genetic algorithm (GA) in conjunction with response surface approaches to improve surface roughness in laser beam cutting CO2 with a continuous wave of SS 304 stainless steel. The effects of the machining parameters, such as cutting speed, nitrogen gas pressure, and focal point location, were investigated quantitatively and optimized. The tests were carried out using the Taguchi L9 orthogonal mesh approach. Analysis of variance, main effect plots, and 3D surface plots were used to evaluate the impact of cutting settings on surface roughness. A multi-objective genetic algorithm in MATLAB was used to achieve a minimum surface roughness of 0.93746 μm, with the input parameters being 2028.712 mm/m cutting speed, 11.389 bar nitrogen pressure, and a focal point position of - 2.499 mm. The optimum results of each method were compared, as the results the response surface approach is less promising than the genetic algorithm method.

Optimal Speed Control Humps Design Based on Driver Comfort

The purpose of this study is to optimise the different speed control humps by considering the vertical and horizontal acceleration of the driver’s head. In previous researches, the main focus was only on vertical acceleration, but in this study, horizontal acceleration of the head is also considered. Here, the root mean square (RMS) of acceleration of head is considered as a measure of occupant comfort. The modelling is performed by a non-linear half-car suspension system (4-DOF) with a linear model of a driver (10-DOF) and a seat. The hamps under study are circular, sinusoidal, half-sinusoidal, and trapezoidal. Finally, by analysing the results, the optimal design of each type of hump is performed. The objective function used is a combination of horizontal and vertical acceleration which is performed using MATLAB genetic algorithm. The results show a significant reduction in horizontal and vertical acceleration at all speeds. From this modelling, it is possible to extract a suitable range for passing the speed of cars over different types of humps. In this study, it is shown that the acceleration values for the circular and half-sinusoidal humps at all speeds are quite close to each other.

Dynamic optimization of solar‐wind hybrid system connected to electrical battery or hydrogen as an energy storage system

Nowadays, due to the pollution arising from the consumption of fossil fuels, destructive effects of pollutants on humans and the environment, and the reduction of reserves of these energy resources, the tendency to utilize renewable energy to meet energy needs has increased. In this investigation, first, a grid-connected photovoltaic-wind-battery (PWB) hybrid system for an educational building is designed and optimized by implementing a genetic algorithm in MATLAB. The main goal is to minimize the annual total cost (ATC) and find the optimal sizes. The balance between the high costs of renewable electricity generation and the setting up a renewable system is achieved by applying the renewable energy fraction (fRE). In the second part, a photovoltaic-wind-fuel cell (PWF) hybrid system is designed and optimized in the same approach. A novel techno-economic-environmental comparison is performed to select the battery bank or hydrogen system as energy storage. Considering the environmental penalties, the effect of the environmental cost on the optimal sizes of components and annual total costs is investigated. Owing to the low tariff of the grid electricity as well as the high cost of the renewable systems, results confirms that the use of renewable systems is not cost-effective. Also, if the authorities and householders intend to implement a storage system to store electricity, battery bank is less expensive than fuel cell system. To apply scenarios to increase renewable energy penetration, a comprehensive sensitivity analysis on the ATCs and optimal sizes is conducted technically and economically. Highlights Designing, optimizing, and comparing of PWB and PWF systems are investigated GA in MATLAB is implemented to determine optimal sizes and minimum ATCs A comprehensive sensitivity analysis is performed on the ATCs and optimal sizes The installing of the hybrid systems with the current tariffs is not cost effective Superiority of the battery bank over the hydrogen system in residential storage

Carbon fibre composite development for in-ground UAV’s with NACA0012 aerofoil wing

A carbon fibre reinforced polymer is designed for NACA0012 airfoil wing using a finite element model to determine the stresses and deformation by considering the aerodynamic loads from wind tunnel testing. The composite airfoil is designed for the use in morphing wings which are known to increase the aerodynamic efficiency of unmanned aerial vehicles. This paper deals with the design procedures of modelling a composite wing using different design variables in conformance to the first order shear deformation theory using ANSYS® 19.2 and optimizing the design by using a fourth degree polynomial found by surface fitting and genetic algorithm in MATLAB® R2020a. The analysis is carried out on 125 samples consisting of different materials, orientation and thickness. The pressure loads found from the wind tunnel testing was converted using weighted average method and applied in ANSYS® 19.2. While designing the airfoil, monocoque concept is used for structural integrity and this is implemented by the usage of Styrene acrylonitrile at the leading and trailing edges which has high strength to weight ratio. The composite laminae with a certain orientation and thickness is found to have the lowest deformation of 158 nm in response to the aerodynamic load.

Lightweight Design and Dynamics Analysis of ZYL‐15000D Directional Drill Reducer

Since the output torque of the rotary reducer of the ZYL‐15000D‐kilometer directional drill is proportional to the gear train transmission ratio, the output torque is large enough when the input speed and output speed meet the design goal. This paper selects the method of reducing the transmission ratio to optimize the size parameters of the reducer. MATLAB genetic algorithm is used in the optimization design, and the minimum volume of the rotary part reducer is taken as the objective of optimization design, while the design variables and constraints are determined. The optimal value of design variables was obtained through optimization, and the parameter values of each gear were determined accordingly. Through analysis, the total volume of the optimized gear reducer was reduced by 49.6%. Then, the 3D model of the optimized gear was created, and the analysis of the transient dynamics of the optimized gear was carried out with ANSYS Workbench software. According to the analysis results, the optimized gear met the strength requirements and provided a reference for the subsequent optimization design of other types of gear reducers.

Solution to the economic dispatch problem of the Nigerian power system using genetic algorithm

This paper aims to solve the economic dispatch problem of the 28-bus Nigerian power system using genetic algorithm. The power flow solution of the network is first obtained using Newton-Raphson technique; the solution thus obtained is used to determine the loss coefficients of the network. For this study, a forecasted load demand of 2000MW will be considered, MATLAB's genetic algorithm optimization toolbox is used to obtain the optimum generation level of each unit. The optimal power output of each scheduled generating units was obtained after 200 iterations at a minimal generation cost of ₦136,370.205/hr. A power loss of 11.32MW in the network was also obtained using Kron's loss formula. Keywords: Genetic Algorithm, Economic Dispatch, loss coefficient, Optimization, Constraint

Finding susceptible areas for a 50 MW solar thermal power plant using 4E analysis and multiobjective optimization

In the present study, a power plant design was first carried out using thermo flow software. Energy, exergy, economic, environmental, and economic (4E) analyses were carried out to supply 50 MW solar power. Using solar energy throughout the year, the amount of reducing atmospheric pollutants, reducing the consumption of fossil fuels, reducing the cost of electricity production, the amount of energy produced and exergy, the amount of exergy destruction, the rate of application and efficiency of the power plant have been obtained. Finally, the proposed cycle is optimized multi-objectively, using genetic algorithm in MATLAB. The results show that the use of solar power plants significantly reduces atmospheric pollutants by 1,559,990.6 tons per year, reducing fossil fuel consumption by 47,143.9 tons per year, and significantly reducing energy consumption despite the low cost of energy carriers in Iran. Also, according to the results, the central regions of Iran are much more suitable for the construction of the power plant, which can generate annual sales of 37,356,480$ per year. The use of solar energy increases the relative cost of the project to significantly reduce the amount of fuel consumed, which ultimately includes a faster return on investment. Finally, it can be argued that the use of the solar thermal power plant is justified from energy, exergy, economic, and environmental. It should be noted that the increase of $$\eta_{{\text{isen,ST}}}$$ will require an increase in initial investment to use higher technologies in the turbine, so increasing the level of equipment technology to increase efficiency to 88% is reasonable and will not be more than that.

Optimal Location of Multiple Tuned Mass Dampers in Regular and Irregular Tall Steel Buildings Plan

Tuned mass dampers are one of the most common devices for the passive control of structures subjected to earthquakes. The structure of these dampers consists of three main parameters: mass, damping, and stiffness. Tuned mass dampers reduce the amplitude of the responses affecting on a mode. In most cases, only a single TMD (tuned mass damper) or a few dampers at several points above the building height are installed on the roof of the building, requiring considerable mass and space in some parts of the structure as overhead. It is also more important to predict the elements that will meet the required mass. In this research, the performance of multiple tuned mass dampers (MTMDs) is investigated in L- and U-shaped regular and irregular tall steel buildings with 10 and 20 floors, under the near- and far-field records. Nonlinear time history analysis is also applied to evaluate the multiple tuned mass dampers effects on the seismic responses of the structures. The SAP2000 API and MATLAB genetic algorithm are used to determine the optimal location of the MTMDs in the roof plans of the buildings. The results show the effects of multiple tuned mass dampers in reducing the seismic response of acceleration, displacement, and base shear up to 50, 40, and 40% in average, respectively. The results of determining the optimum location of MTMDs in the models indicate the importance of the symmetry of the dampers relative to the centre of mass of the building.

Optimization of water distribution networks using developed binary genetic algorithm and hydraulic model software

The optimal design of urban water distribution networks is a significant issue that has been of critical interest in the water industry for many years. The optimal design of the distribution network aims to find the best solution for transferring water from the reservoir to consumers at the lowest cost. In this study, optimization of the water distribution network (ZONE 1 of Ilam city, Iran) was performed using the fast messy genetic algorithms (FMGA) tool in the hydraulic model for three different pipe networks. Also, these networks were optimized by using a combination of EPANET and an in-house developed binary genetic algorithm in MATLAB. The costs of the optimized hydraulic networks of polyethylene and polypropylene pipes were lower, respectively, by 20.56 % and 52.94 % compared to the consulting company's original designs, while for the glass fiber reinforced plastic pipe (GRP) pipe network the cost increased by 12.61 %. Also, the results of a developed algorithm for polyethylene pipe decreased by 22.13 %.

Structural Optimization for Asymmetric Framed Structures without Shear Walls

This paper proposes a method for the preliminary arrangement of columns having variable sizes on an asymmetric plan, such that the resulting structure will have minimum torsion. Asymmetry can be due to shape of the plan as well as arrangement of columns having variable sizes. This study shows the influence of first three modes in determining the structural behavior of RCC framed buildings during earthquake. The time periods were approximately calculated by using 3D-shear-torsion beam method. The optimization was done using Genetic algorithm in Matlab. The seismic performance of general asymmetric structures with uniform square columns were compared with optimized asymmetric structures having columns with variable sizes. The results from pushover analysis showed significant increase in strength and ductility along the direction having torsion.

Comfort optimization of a new type of foot mechanism for lower extremity exoskeleton

In order to reduce the impact caused by the contact between the foot and the ground when wearing the lower extremity exoskeleton under the condition of high load, this paper proposed an exoskeleton foot mechanism for improving the foot comfort, and optimized the key index of its influence on the comfort. Firstly, the physical model of foot mechanism was established based on the characteristics of foot stress in gait period, and then the mathematical model of vibration was abstracted. The correctness of the model was verified by the finite element analysis software ANSYS. Then, this paper analyzed the influence of vibration parameters on absolute transmissibility based on vibration mathematical model, and optimized vibration parameters with MATLAB genetic algorithm toolbox. Finally, this paper took white noise to simulate the road elevation as the vibration input, and used the visual simulation tool Simulink in MATLAB and the vibration equation to construct the acceleration simulation model, and then calculated the vibration weighted root mean square acceleration value of the foot. The results of this study show that this foot comfort mechanism can meet the comfort indexes of vibration absorption and plantar pressure, and this paper provides a relatively complete method for the design of exoskeleton foot mechanism, which has reference significance for the design of other exoskeleton foot and ankle joint rehabilitation mechanism.

Development and validation of constraints handling in a Differential Evolution optimizer

Research work requires independent, portable optimization tools for many applications, most often for problems where derivability of objective functions is not satisfied. Differential evolution optimization represents an alternative to the more complex, encryption based genetic algorithms. Various packages are available as freeware, but they lack constraints handling, while constrained optimizations packages are commercially available. However, the literature devoted to constraints treatment is significant and the current work is devoted to the implementation of such an optimizer, to be applied in low-fidelity optimization processes. The parameter free penalty scheme is adopted for implementation, and the code is validated against the CEC2006 benchmark test problems and compared with the genetic algorithm in MATLAB. Our paper underlines the implementation of constrained differential evolution by varying two parameters, a predefined parameter for feasibility and the scaling factor, to ensure the convergence of the solution.