scholarly journals Investigation on Evolutionary Computation Techniques of a Nonlinear System

2011 ◽  
Vol 2011 ◽  
pp. 1-21 ◽  
Author(s):  
Tran Trong Dao
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Simulated Annealing ◽  
Nonlinear System ◽  
Dynamic Behaviour ◽  
Batch Process ◽  
Nonlinear Mathematical Model ◽  
Artificial Intelligent ◽  
Simulation And Optimization ◽  
System A

The main aim of this work is to show that such a powerful optimizing tool like evolutionary algorithms (EAs) can be in reality used for the simulation and optimization of a nonlinear system. A nonlinear mathematical model is required to describe the dynamic behaviour of batch process; this justifies the use of evolutionary method of the EAs to deal with this process. Four algorithms from the field of artificial intelligent—differential evolution (DE), self-organizing migrating algorithm (SOMA), genetic algorithm (GA), and simulated annealing (SA)—are used in this investigation. The results show that EAs are used successfully in the process optimization.

scholarly journals Optimization of Refrigeration Rate for a Thermoelectric Cooler in Restricted Space using Stochastic Algorithms

2019 ◽  
Vol 8 (2) ◽  
pp. 2306-2311
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Simulated Annealing ◽  
Heat Exchanger ◽  
Performance Measures ◽  
Structural Parameters ◽  
Electrical Contact ◽  
Stochastic Algorithms ◽  
Thermoelectric Cooler ◽  
Design Variables

In the present study, a mathematical model of single stage thermoelectric cooler (TEC) is reported. This model is then employed to optimize the rate of refrigeration (ROR) which is one of the important performance measures of TEC. Two stochastic algorithms, namely, the genetic algorithm (GA) and simulated annealing (SA) are employed for optimizing the said performance of TEC for restricted space. The selected design variables are the geometric structural parameters of TEC elements and the input current. This study also includes the thermal resistance of hot side heat exchanger and electrical contact resistances into consideration. The results show that these design variables can be optimally set to maximize ROR within restricted space very significantly. The two algorithms for optimization attained almost the same values of design variables that lead to optimum ROR, though the GA could locate multi-modal optimum and hence can be used by the designer to choose among various options of design variables without compromising on the optimized value of ROR.

Mathematical modeling of the HIV/AIDS epidemic in Cuba

2015 ◽  
Vol 08 (04) ◽  
pp. 1550047 ◽  
Author(s):  
Antonio Mastroberardino ◽  
Yuanji Cheng ◽  
Ahmed Abdelrazec ◽  
Hao Liu
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Stability Analysis ◽  
Nonlinear System ◽  
Transmission Dynamics ◽  
Nonlinear Mathematical Model ◽  
Aids Epidemic ◽  
National Prevention ◽  
Mode Of Transmission ◽  
Hiv Aids

In this paper, a nonlinear mathematical model is presented for the transmission dynamics of HIV/AIDS in Cuba. Due to Cuba's highly successful national prevention program, we assume that the only mode of transmission is through contact with those yet to be diagnosed with HIV. We find the equilibria of the governing nonlinear system, perform a linear stability analysis, and then provide results on global stability.

Modeling Heart Rate Dynamics in Response to Changes in Exercise Intensity

2015 ◽  
Author(s):  
Michael J. Mazzoleni ◽  
Claudio L. Battaglini ◽  
Brian P. Mann
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Heart Rate ◽  
Heart Rate Response ◽  
Synthetic Data ◽  
Model Parameters ◽  
Nonlinear Mathematical Model ◽  
Heart Rate Dynamics ◽  
Parameter Values ◽  
Good Agreement

This paper develops a nonlinear mathematical model to describe the heart rate response of an individual during cycling. The model is able to account for the fluctuations of an individual’s heart rate while they participate in exercise that varies in intensity. A method for estimating the model parameters using a genetic algorithm is presented and implemented, and the results show good agreement between the actual parameter values and the estimated values when tested using synthetic data.

Stability Analysis of a Load Sensing Hydraulic Transmission System Modeling and Simulaton Approach

2000 ◽  
Author(s):  
Rana Saha ◽  
Niloy Khutia ◽  
Rathindranath Maiti
Keyword(s):  
Mathematical Model ◽  
Stability Analysis ◽  
Simulation Model ◽  
Hydraulic System ◽  
System Modeling ◽  
Nonlinear Mathematical Model ◽  
System Parameters ◽  
Load Sensing ◽  
System A ◽  
Simulation Results

Abstract An energy saving hydraulic system, known as load-sensing hydraulic system, to improve the efficiency of transmitting power from the pump to load has been studied in the present work. Due to the addition of the load sensing mechanism stability characteristics deteriorate in this system. A nonlinear mathematical model followed by a simulation model using SIMULINK has been developed to study the effect of system parameters on stability. Simulation results are verified with existing theoretical and experimental results.

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.

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

2020 ◽  
pp. 095440542098068
Author(s):  
Kamran Forghani ◽  
S. M. T. Fatemi Ghomi ◽  
Reza Kia
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Model Material ◽  
Virtual Manufacturing ◽  
Superior Performance ◽  
Shop Floor ◽  
Processing Route ◽  
Manufacturing Cells ◽  
Comparison Results ◽  
Virtual Manufacturing Cells

Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

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