scholarly journals STUDYING CHARACTERISTICS OF GENETIC ALGORITHM FOR OPTIMIZING TEMPERATURE REGIME OF HEATED ROOMS

2020 ◽  
Vol 2020 (4) ◽  
pp. 49-61
Author(s):  
Alexander Petrovich Shuravin ◽  
Sergey Valentinovich Vologdin
Keyword(s):  
Genetic Algorithm ◽  
Energy Saving ◽  
Temperature Regime ◽  
Mathematical Formulation ◽  
Mathematical Optimization ◽  
Heating System ◽  
Optimization Methods ◽  
Actual Condition ◽  
Directed Search

The article discusses the problems of energy-saving, which can be solved by using mathematical optimization methods, and the mathematical optimization algorithms related to these problems. There has been given the review of Russian and foreign works on energy saving and energy optimization. The need for solving the problems of optimizing the thermohydraulic regimes of buildings is explained. There is given the mathematical formulation of the problem of optimizing the temperature regime of indoor areas using adjustable devices and two methods for solving the problem: the directed search method and the genetic algorithm. The above algorithms including the mathematical apparatus are described. The objective function is described as the standard deviation of the temperature of the heated rooms. Various options for using the genetic algorithm have been investigated. A modification of the genetic algorithm is proposed, which allows obtaining the best results in relation to the problem under consideration. The results of a computation experiment for the considered optimization methods are presented. The calculations were carried out for a typical building in Izhevsk under average design conditions, taking into account the actual condition of the enclosing structures, the heating system of the building, and heating devices of indoor areas. A comparative analysis of the convergence of the iterative process for various options for the application of the genetic algorithm and directional search has been carried out. It is concluded that the new modification allows us to improve the quality of the genetic algorithm. The dependence of the convergence of the genetic algorithm on its parameters was investigated and a modification of this algorithm was proposed in relation to the problem of optimizing the thermo-hydraulic modes of heated rooms. The study is of practical value in terms of using the proposed methodology of saving heat energy in the system of housing and communal services.Practical value is the ability to use in the housing and communal services to save thermal energy.

Optimized Crossover JumpX in Genetic Algorithm for General Routing Problems

2018 ◽  
pp. 205-230
Author(s):  
Hicham El Hassani ◽  
Said Benkachcha ◽  
Jamal Benhra
Keyword(s):  
Genetic Algorithm ◽  
Optimization Methods ◽  
Search Space ◽  
Optimal Solutions ◽  
Solution Quality ◽  
Path Representation ◽  
Representation Technique ◽  
Hard Problems ◽  
The Traveling Salesman Problem

Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is one of the most studied Supply chain management problems. This paper proposes a new crossover operator called Jump Crossover (JMPX) for solving the travelling salesmen problem using a genetic algorithm (GA) for near-optimal solutions, to conclude on its efficiency compared to solutions quality given by other conventional operators to the same problem, namely, Partially matched crossover (PMX), Edge recombination Crossover (ERX) and r-opt heuristic with consideration of computational overload. We adopt the path representation technique for our chromosome which is the most direct representation and a low mutation rate to isolate the search space exploration ability of each crossover. The experimental results show that in most cases JMPX can remarkably improve the solution quality of the GA compared to the two existing classic crossover approaches and the r-opt heuristic.

Genetic Algorithm Learning of Nash Equilibrium

2015 ◽  
Vol 13 (3) ◽  
pp. 1-14 ◽  
Author(s):  
M'hamed Outanoute ◽  
Mohamed Baslam ◽  
Belaid Bouikhalene
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Quality Of Service ◽  
Nash Equilibrium ◽  
Service Providers ◽  
Optimization Methods ◽  
Great Power ◽  
Dynamical Behaviors ◽  
Game Theoretic

To select or change a service provider, customers use the best compromise between price and quality of service (QoS). In this work, the authors formulate a game theoretic framework for the dynamical behaviors of Service Providers (SPs). They share the same market and are competing to attract more customers to gain more profit. Due to the divergence of SPs interests, it is believed that this situation is a non-cooperative game of price and QoS. The game converges to an equilibrium position known Nash Equilibrium. Using Genetic Algorithms (GAs), the authors find strategies that produce the most favorable profile for players. GAs are from optimization methods that have shown their great power in the learning area. Using these meta-heuristics, the authors find the price and QoS that maximize the profit for each SP and illustrate the corresponding strategy in Nash Equilibrium (NE). They also show the influence of some parameters of the problem on this equilibrium.

scholarly journals Inversion of seismic refraction data using genetic algorithms

Geophysics ◽  
1996 ◽  
Vol 61 (6) ◽  
pp. 1715-1727 ◽  
Author(s):  
Fabio Boschetti ◽  
Mike C. Dentith ◽  
Ron D. List
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Seismic Refraction ◽  
Solution Space ◽  
Optimization Methods ◽  
Data Set ◽  
Weathered Layer ◽  
Seismic Refraction Data ◽  
Refraction Data

The use of genetic algorithms in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the nonlinearity inherent in such applications. However, in their application to specific problems, as with all algorithms, problems of implementation arise. After extensive numerical tests, we implemented a genetic algorithm to efficiently invert several sets of synthetic seismic refraction data. In particular, we aimed at overcoming one of the main problems in the application of genetic algorithms to geophysical problems: i.e., high dimensionality. The addition of a pseudo‐subspace method to the genetic algorithm, whereby the complexity and dimensionality of a problem is progressively increased during the inversion, improves the convergence of the process. The method allows the region of the solution space containing the global minimum to be quickly found. The use of local optimization methods at the last stage of the search further improves the quality of the inversion. The genetic algorithm has been tested on a field data set to determine the structure and base of the weathered layer (regolith) overlaying a basement of granite and greenstones in an Archaean terrain of Western Australia.

scholarly journals Comparison of the characteristics of the genetic algorithm and the method of coordinates search for optimization of temperature modes indoor areas

2019 ◽  
pp. 260-270
Author(s):  
A P Shuravin ◽  
S V Vologdin
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Computational Experiment ◽  
Mathematical Formulation ◽  
Computational Cost ◽  
Optimization Methods ◽  
Search Method ◽  
Mathematical Apparatus ◽  
Temperature Mode ◽  
Project Smart

The article substantiates the relevance of optimization algorithms research for solving various applied problems and for the science of artificial intelligence. The need to solve problems of optimizing the thermal-hydraulic modes of buildings (as part of the project "Smart City") is explained. The paper presents a mathematical formulation of the problem of optimizing the temperature mode of rooms using adjustable devices. Existing work provides two methods for solving the posed problem. They are the coordinates search method and the genetic algorithm. The article contains the description of the above mentioned algorithms (including the mathematical apparatus used). The results of the computational experiment (for the considered optimization methods) are presented. These experimental results show that the genetic algorithm provides better optimization results than the coordinates search method, but it has a large computational cost. The hypothesis was confirmed that in order to increase the efficiency of solving the considered class of problems it is necessary to combine the genetic algorithm and the coordinates search method.

scholarly journals STUDIES OF JOINT WORK OF GENETIC ALGORITHM AND COORDINATE SEARCH ALGORITHM TO OPTIMIZE TEMPERATURE OF HEATED INDOOR AREAS

2019 ◽  
pp. 59-69
Author(s):  
Alexander Petrovich Shuravin ◽  
Sergey Valentinovich Vologdin
Keyword(s):  
Genetic Algorithm ◽  
Thermal Energy ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Thermal Power ◽  
Mathematical Formulation ◽  
Gradient Methods ◽  
Optimization Methods ◽  
Search Method ◽  
Component Element

The article is focused on studying optimization algorithms that are relevant both for solving applied problems and for studying the artificial intelligence in general. Optimization methods are used to solve environmental problems including the issues of energy saving. It is important to solve problems of optimizing the thermo-hydraulic modes of buildings (as a part of the “Smart City” project), in particular, problems of eliminating temperature imbalance in terms of saving thermal energy and improving the microclimate in apartments. There is shown a mathematical formulation of the problem of optimizing the temperature modes of the indoor areas using adjustable devices. A hybrid algorithm applied to solve the problem has been described. The considered algorithm combines two optimization methods: a coordinate search method and a genetic algorithm. Thus, the stochastic component (element of the genetic algorithm) and the gradient component (element of the coordinate search method) are used in the hybrid algorithm. A description of the above algorithms is given including the mathematical apparatus used and the design formulas. The results of the numerical experiment for the suggested algorithm are presented. These results are compared with the results of applying the genetic algorithm and the method of coordinates search separately. There has been confirmed the hypothesis that in order to increase the efficiency of solving the considered class of problems, it is necessary to combine the genetic algorithm and gradient methods. At the same time, it has been inferred that in cases of low thermal power of radiators, optimization of the hydraulic resistance of valves is not sufficient, thermal insulation measures and replacement of radiators are also required. The practical value of the work lies in the possibility of solving the problem of saving thermal energy in the housing and communal services system.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

Software suite for determining the tilts of tower-type structures according to terrestrial laser scanning

2020 ◽  
Vol 961 (7) ◽  
pp. 2-7
Author(s):  
A.V. Zubov ◽  
N.N. Eliseeva
Keyword(s):  
Laser Scanning ◽  
Optimization Problems ◽  
Optimization Methods ◽  
User Participation ◽  
Software Suite ◽  
Current State ◽  
Visual Basic For Applications ◽  
Operational Data ◽  
Theoretical Developments

The authors describe a software suite for determining tilt degrees of tower-type structures according to ground laser scanning indication. Defining the tilt of the pipe is carried out with a set of measured data through approximating the sections by circumferences. They are constructed using one of the simplest search engine optimization methods (evolutionary algorithm). Automatic filtering the scan of the current section from distorting data is performed by the method of assessing the quality of models constructed with that of least squares. The software was designed using Visual Basic for Applications. It contains several blocks (subprograms), with each of them performing a specific task. The developed complex enables obtaining operational data on the current state of the object with minimal user participation in the calculation process. The software suite is the result of practical implementing theoretical developments on the possibilities of using search methods at solving optimization problems in geodetic practice.

scholarly journals Energy Saving and Charging Discharging Characteristics of Multiple PCMs Subjected to Internal Air Flow

Fluids ◽  
2021 ◽  
Vol 6 (8) ◽  
pp. 275
Author(s):  
Ahmed J. Hamad
Keyword(s):  
Phase Change ◽  
Energy Saving ◽  
Air Temperature ◽  
Temperature Control ◽  
Phase Change Materials ◽  
Energy Savings ◽  
Heating System ◽  
Air Heating ◽  
Room Model ◽  
Model Temperature

One essential utilization of phase change materials as energy storage materials is energy saving and temperature control in air conditioning and indirect solar air drying systems. This study presents an experimental investigation evaluating the characteristics and energy savings of multiple phase change materials subjected to internal flow in an air heating system during charging and discharging cycles. The experimental tests were conducted using a test rig consisting of two main parts, an air supply duct and a room model equipped with phase change materials (PCMs) placed in rectangular aluminum panels. Analysis of the results was based on three test cases: PCM1 (Paraffin wax) placed in the air duct was used alone in the first case; PCM2 (RT–42) placed in the room model was used alone in the second case; and in the third case, the two PCMs (PCM1 and PCM2) were used at the same time. The results revealed a significant improvement in the energy savings and room model temperature control for the air heating system incorporated with multiple PCMs compared with that of a single PCM. Complete melting during the charging cycle occurred at temperatures in the range of 57–60 °C for PCM1 and 38–43 °C for PCM2, respectively, thereby validating the reported PCMs’ melting–solidification results. Multiple PCMs maintained the room air temperature at the desired range of 35–45.2 °C in the air heating applications by minimizing the air temperature fluctuations. The augmentation in discharging time and improvement in the room model temperature using multiple PCMs were about 28.4% higher than those without the use of PCMs. The total energy saving using two PCMs was higher by about 29.5% and 46.7% compared with the use of PCM1 and PCM2, respectively. It can be concluded that multiple PCMs have revealed higher energy savings and thermal stability for the air heating system considered in the current study.

scholarly journals Adjustment of Olive Fruit Temperature before Grinding for Olive Oil Extraction. Experimental Study and Pilot Plant Trials

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 586
Author(s):  
Eddy Plasquy ◽  
José María García Martos ◽  
María del Carmen Florido Fernández ◽  
Rafael Rubén Sola-Guirado ◽  
Juan Francisco García Martín
Keyword(s):  
Heat Treatment ◽  
Pilot Plant ◽  
Heating System ◽  
Oil Extraction ◽  
Warm Up ◽  
Precise Adjustment ◽  
Olive Cultivars ◽  
Plant Trials ◽  
Washing Water

Harvesting at high temperatures and bulk transport can negatively influence the quality of olives and lead to undesirable alterations in the extracted oil. Cooling the fruit in the field would be the most logical solution, but it means that the olives arrive too cold at the mill for immediate processing. In this work, the use of warm water in the washing tub to warm up the fruit before grinding instead of flash heat treatment on the paste was assessed in two experiments. In the first one, at the laboratory level, the temperature after milling was determined in three olive cultivars, previously stored at 5 or 10 °C, and then submerged at different water temperatures (25, 30, and 35 °C) for 15, 30, 45, and 60 s. In the second one, two batches of olives were cooled in the field at 5 °C and then conditioned with washing water to obtain a paste at the entrance of the pilot plant malaxer at 27 °C. The temperature of the olives was measured at five points from the discharging up to their entering, as paste, into the malaxer. The results demonstrated the feasibility of the method as the temperature of the ground olives was kept at the desired temperature (28 ± 1 °C). The trials highlight the potential for automating an even more precise adjustment of the temperature of the olives before milling once the washing tub is equipped with a safe heating system.

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