Research on cargo-loading optimization based on genetic and fuzzy integration

2021 ◽  
Vol 40 (4) ◽  
pp. 8493-8500
Author(s):  
Yanwei Du ◽  
Feng Chen ◽  
Xiaoyi Fan ◽  
Lei Zhang ◽  
Henggang Liang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Three Dimensional ◽  
Distribution Center ◽  
Long Time ◽  
Low Efficiency ◽  
Decision Making Model ◽  
The Mathematical Model ◽  
Loading Scheme

With the increase of the number of loaded goods, the number of optional loading schemes will increase exponentially. It is a long time and low efficiency to determine the loading scheme with experience. Genetic algorithm is a search heuristic algorithm used to solve optimization in the field of computer science artificial intelligence. Genetic algorithm can effectively select the optimal loading scheme but unable to utilize weight and volume capacity of cargo and truck. In this paper, we propose hybrid Genetic and fuzzy logic based cargo-loading decision making model that focus on achieving maximum profit with maximum utilization of weight and volume capacity of cargo and truck. In this paper, first of all, the components of the problem of goods stowage in the distribution center are analyzed systematically, which lays the foundation for the reasonable classification of the problem of goods stowage and the establishment of the mathematical model of the problem of goods stowage. Secondly, the paper abstracts and defines the problem of goods loading in distribution center, establishes the mathematical model for the optimization of single car three-dimensional goods loading, and designs the genetic algorithm for solving the model. Finally, Matlab is used to solve the optimization model of cargo loading, and the good performance of the algorithm is verified by an example. From the performance evaluation analysis, proposed the hybrid system achieve better outcomes than the standard SA model, GA method, and TS strategy.

Simulation Investigation on Environment-Induced Pitting Corrosion on the Metal Surface

2021 ◽  
Vol 13 (5) ◽  
pp. 820-828
Author(s):  
Wei Zhang ◽  
Shengli Lv ◽  
Leijiang Yao ◽  
Xiaoyan Tong
Keyword(s):  
Mathematical Model ◽  
Pitting Corrosion ◽  
Three Dimensional ◽  
Corrosion Damage ◽  
Sudden Onset ◽  
Ion Concentration ◽  
Two Dimensional Image ◽  
Aging Aircraft ◽  
Efficient Calculation ◽  
The Mathematical Model

The prediction of corrosion damage is one of effective research methods in the safety inspection of aging aircraft structures. A mathematical model for quantifying corrosion damage is used in this paper to predict the onset of corrosion on structural surfaces exposed to aggressive environments. Based on the finite difference technique, the evolution process of local pitting corrosion on the surface of aluminum alloy in the medium is simulated, which can consider the sudden onset and the randomness of pitting corrosion. The effect of local ion concentration and oxide film damage on subsequent pitting nucleation was analyzed. Based on the efficient calculation program, the effectiveness of the mathematical model is verified by the comparison between the corrosion damage morphology and the experimental data in the literature. The results show a more widespread distribution of subsequent pits because of stronger aggressive ions are released during the life cycle of active pits and the higher diffusion coefficient of the aggressive ions. The three dimensional morphology is generated by image processing method based on the gray value of the two dimensional image of pits.

Genetic Algorithm Optimization of a Double Four-Bar Manipulator

2013 ◽  
Vol 834-836 ◽  
pp. 1323-1326
Author(s):  
Qi Jing Tang ◽  
Tie Shi Zhao
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Structural Strength ◽  
Optimization Method ◽  
Installation Space ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Transmission Angle ◽  
The Mathematical Model

In order to optimize the dimension of a manipulator, the optimization requirements are analyzed. Then the mathematical model and optimization objectives are established. Next, the lengths of the manipulator are optimized by Matlab genetic algorithm optimization toolbox. The structural strength and bearing installation space are considered at the same time. The trajectory and transmission angle are compared. Finally, the lengths which meet the use requirements are obtained. This optimization method provides a reference for similar mechanism.

scholarly journals Enzyme-Based Biosensors: Tackling Electron Transfer Issues

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3517 ◽  
Author(s):  
Paolo Bollella ◽  
Evgeny Katz
Keyword(s):  
Mathematical Model ◽  
Electron Transfer ◽  
Fuel Cells ◽  
Glucose Oxidase ◽  
Rate Constant ◽  
Direct Electron Transfer ◽  
Redox Enzymes ◽  
Practical Applications ◽  
The Mathematical Model

This review summarizes the fundamentals of the phenomenon of electron transfer (ET) reactions occurring in redox enzymes that were widely employed for the development of electroanalytical devices, like biosensors, and enzymatic fuel cells (EFCs). A brief introduction on the ET observed in proteins/enzymes and its paradigms (e.g., classification of ET mechanisms, maximal distance at which is observed direct electron transfer, etc.) are given. Moreover, the theoretical aspects related to direct electron transfer (DET) are resumed as a guideline for newcomers to the field. Snapshots on the ET theory formulated by Rudolph A. Marcus and on the mathematical model used to calculate the ET rate constant formulated by Laviron are provided. Particular attention is devoted to the case of glucose oxidase (GOx) that has been erroneously classified as an enzyme able to transfer electrons directly. Thereafter, all tools available to investigate ET issues are reported addressing the discussions toward the development of new methodology to tackle ET issues. In conclusion, the trends toward upcoming practical applications are suggested as well as some directions in fundamental studies of bioelectrochemistry.

Mathematical modeling of a generic multi-profile form milling cutter

2012 ◽  
Vol 227 (5) ◽  
pp. 1036-1046 ◽  
Author(s):  
Mohammed Rajik Khan ◽  
Puneet Tandon
Keyword(s):  
Mathematical Model ◽  
Three Dimensional ◽  
Sculptured Surfaces ◽  
Three Dimensional Model ◽  
Machining Time ◽  
Milling Cutter ◽  
Machined Parts ◽  
Rotary Cutting ◽  
Three Dimensional Models ◽  
The Mathematical Model

In order to machine multiple sculptured surfaces with reduced machining time and high accuracy of the machined parts, shape design of a customised multi-point rotary cutting tool needs to be evolved. In the present work, a novel design of a generic multi-profile form milling cutter is developed for machining various multiple sculptured surfaces. This article describes in detail the mathematical model to design an accurate three-dimensional geometry of a generic multi-profile form milling cutter. Use of non-uniform rational B-spline curve(s) and sweep surfaces enables to control the shape of cutting flutes of the generic multi-profile form milling cutter. The article also discusses the methodology to develop a variety of cutters lying in the same conceptual family of multi-profile form milling cutter. To physically visualise the cutter and to show one of the downstream applications once a three-dimensional model of the cutter is available, one of the multi-profile form milling cutters is fabricated. The proposed methodology offers an intuitive high-quality mathematical model for a generic family of multi-profile form milling cutters, which is different from the traditional three-dimensional models.

Computations of Three-Dimensional Gas-Turbine Combustion Chamber Flows

1979 ◽  
Vol 101 (3) ◽  
pp. 326-336 ◽  
Author(s):  
M. A. Serag-Eldin ◽  
D. B. Spalding
Keyword(s):  
Mathematical Model ◽  
Turbulent Flows ◽  
Combustion Process ◽  
Three Dimensional ◽  
Solution Algorithm ◽  
Physical Models ◽  
Turbulence Energy ◽  
Experimental Conditions ◽  
Diffusion Controlled ◽  
The Mathematical Model

The paper presents a mathematical model for three-dimensional, swirling, recirculating, turbulent flows inside can combustors. The present model is restricted to single-phase, diffusion-controlled combustion, with negligible radiation heat-transfer; however, the introduction of other available physical models can remove these restrictions. The mathematical model comprises differential equations for: continuity, momentum, stagnation enthalpy, concentration, turbulence energy, its dissipation rate, and the mean square of concentration fluctuations. The simultaneous solution of these equations by means of a finite-difference solution algorithm yields the values of the variables at all internal grid nodes. The prediction procedure, composed of the mathematical model and its solution algorithm, is applied to predict the fields of variables within a representative can combustor; the results are compared with corresponding measurements. The predicted results give the same trends as the measured ones, but the quantitative agreement is not always acceptable; this is attributed to the combustion process not being truly diffusion-controlled for the experimental conditions investigated.

Intelligent Generating Examination Paper from Item Bank Based on Improved Genetic Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 3637-3640
Author(s):  
Li Feng ◽  
Qian Wu ◽  
Jing Shao Zhang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Computational Study ◽  
Item Bank ◽  
Test Paper ◽  
Improved Genetic Algorithm ◽  
Fitness Evaluation ◽  
Simulation Results ◽  
The Mathematical Model ◽  
Examination Paper

In this paper, we analyze the disadvantage of common generating test paper algorithm. An improved genetic algorithm (IGA) is proposed and used in auto-generating examination paper algorithm. We design the mathematical model of auto-generating test paper algorithm and improved the traditional GA fitness evaluation form. A computational study is carried out to verify the algorithm. Simulation results demonstrate that the performance of IGA can work efficiently than traditional ones.

Calculations of three-dimensional viscous flow in a multiblade centrifugal fan by modelling blade forces

2003 ◽  
Vol 217 (3) ◽  
pp. 287-297 ◽  
Author(s):  
S-J Seo ◽  
K-Y Kim ◽  
S-H Kang
Keyword(s):  
Mathematical Model ◽  
Turbulent Flows ◽  
Numerical Study ◽  
Three Dimensional ◽  
Navier Stokes ◽  
Centrifugal Fan ◽  
Complex Flows ◽  
Flow Through ◽  
Volume Method ◽  
The Mathematical Model

A numerical study is presented for Reynolds-averaged Navier-Stokes analysis of three-dimensional turbulent flows in a multiblade centrifugal fan. Present work aims at development of a relatively simple analysis method for these complex flows. A mathematical model of impeller forces is obtained from the integral analysis of the flow through the impeller. A finite volume method for discretization of governing equations and a standard k-ɛ model as turbulence closure are employed. For the validation of the mathematical model, the computational results for velocity components, static pressure, and flow angles at the exit of the impeller were compared with experimental data. The comparisons show generally good agreement, especially at higher flow coefficients.

scholarly journals Solution of Fractional Order System of Bagley-Torvik Equation Using Evolutionary Computational Intelligence

2011 ◽  
Vol 2011 ◽  
pp. 1-18 ◽  
Author(s):  
Muhammad Asif Zahoor Raja ◽  
Junaid Ali Khan ◽  
Ijaz Mansoor Qureshi
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Mathematical Model ◽  
Fractional Order ◽  
Computational Intelligence ◽  
Pattern Search ◽  
Fractional Order System ◽  
Order System ◽  
Search Technique ◽  
The Mathematical Model

A stochastic technique has been developed for the solution of fractional order system represented by Bagley-Torvik equation. The mathematical model of the equation was developed with the help of feed-forward artificial neural networks. The training of the networks was made with evolutionary computational intelligence based on genetic algorithm hybrid with pattern search technique. Designed scheme was successfully applied to different forms of the equation. Results are compared with standard approximate analytic, stochastic numerical solvers and exact solutions.

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