Browsing by Subject "genetic algorithm"

Now showing 1 - 14 of 14

Access status: Open Access ,
A new empirical correlation for estimating bubble point pressure using the genetic algorithm
(Wydawnictwa AGH, 2017) Heidarian, Mohamad; Karimnezhad, Masoud; Schaffie, Mahin; Ranjbar, Mohammad
In this paper, a new and more accurate correlation to predict bubble point pressure (P$_{b}$) for Middle East crudes by using the genetic algorithm (GA) is attempted. For this purpose, a total of 286 data sets of different crude oils from Middle East reservoirs were used as training data for constructing the correlation. The general form of the correlation was found by several regressive examinations. To improve the correlation, the genetic algorithm was applied. To validate the correlation, 143 data sets of different crudes from Middle East reservoirs which were different from the training data were used as test data for calculating mean absolute relative error (MARE) and correlation coefficient (R$^{2}$) between the predicted values from the proposed correlation and the experimental values. In addition, the MARE and R$^{2}$ were calculated for previous correlation in the test data. The results show that the proposed correlation is more accurate than all of the previous correlations exclusively for Middle East crudes.
Access status: Open Access ,
Algorytm genetyczny dla problemu gniazdowego z ograniczeniem bez czekania
(Wydawnictwa AGH, 2005) Makuchowski, Mariusz
W pracy analizuje się problem gniazdowy z ograniczeniem bez czekania z kryterium optymalizacji będącym terminem zakończenia wykonywania wszystkich zadań. Przedstawia się klasę rozwiązań superaktywnych oraz jej rozszerzenie - klasę rozwiązań pseudoaktywnych. Na bazie omówionych klas rozwiązań proponuje się dwa algorytmy genetyczne. Jakość proponowanych algorytmów ocenia się na podstawie przeprowadzonych badań numerycznych, wykorzystując literaturowe przykłady testowe.
Access status: Restricted ,
Algorytm genetyczny z dynamicznym doborem parametrów sterujących
(Data obrony: 2017-01-20) Urbańczyk, Wiktor
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
Application of an memetic algorithm to placement of sensors for active noise-vibration control
(2013) Wrona, Stanisław; Pawełczyk, Marek
For successful active control of a vibrating structure it is essential to appropriately place sensors. One of the most important criteria is to make the system observable, so any control objectives can be achieved. In this paper the observability-oriented placement of sensors is undertaken. First, a theoretical model of a fully clamped plate is presented. Optimization criterion based on maximization of observability of the system is developed. A memetic algorithm is used to find the optimal solution. Obtained results are compared with those obtained by the genetic algorithm.The configuration is also validated experimentally.
Access status: Open Access ,
Automatyczna mutacja w algorytmach ewolucyjnych
(Wydawnictwa AGH, 2009) Makuchowski, Mariusz; Tyński, Adam
In this paper a general method for determining a probability of mutation in evolutionary algorithms is given. The presented method if illustrated by a genetic algorithm for no wait job shop problem. We compare experimentally a classical evolutionary algorithm with parameters determined in a standard way with an evolutionary algorithm equipped with the proposed method.
Access status: Open Access ,
Meta-heuristic approach based on genetic and greedy algorithms to solve flexible job-shop scheduling problem
(Wydawnictwa AGH, 2021) Rezaeipanah, Amin; Sarhangnia, Fariba; Abdollahi, Mohammad Javad
Job-shop scheduling systems are one of the applications of group technology in industry, the purpose of which is to take advantage of the physical or operational similarities of products in their various aspects of construction and design. Additionally, these systems are identified as cellular manufacturing systems (CMS). In this paper, a meta-heuristic method that is based on combining genetic and greedy algorithms has been used in order to optimize and evaluate the performance criteria of the flexible job-shop scheduling problem. In order to improve the efficiency of the genetic algorithm, the initial population is generated by the greedy algorithm, and several elitist operators are used to improve the solutions. The greedy algorithm that is used to improve the generation of the initial population prioritizes the cells and the job in each cell and, thus, offers quality solutions. The proposed algorithm is tested over the P-FJSP dataset and compared with the state-of-the-art techniques of this literature. To evaluate the performance of the diversity, spacing, quality, and run-time criteria were used in a multi-objective function. The results of the simulation indicate the better performance of the proposed method as compared to the NRGA and NSGA-II methods.
Access status: Open Access ,
Minimalizacja czasu cyklu wytwarzania na linii. Podejście genetyczne z ekspresją genów
(Wydawnictwa AGH, 2005) Pempera, Jarosław; Smutnicki, Czesław
Praca poświęcona jest deterministycznemu wariantowi problemu optymalizacji przebiegu cyklu wytwórczego w przepływowym systemie wytwarzania powtarzalnego z ograniczeniami składowania. Celem optymalizacji jest wyznaczenie harmonogramu cyklu, na który składają się kolejność wykonywania zadań oraz terminy czasowe rozpoczęcia zadań dla tej kolejności. W pracy przedstawiono modele problemu i pewne jego własności oraz zaproponowano nowej klasy algorytm genetyczny z tzw. ekspresją genów, wykorzystujący nadmiarową informację genetyczną pochodzącą nie tylko od rodziców, ale też od przodków. Przedstawiono wyniki obliczeniowe dla przykładów testowych Taillarda.
Access status: Open Access ,
Modelowanie efektywności reklamy
(Wydawnictwa AGH, 2007) Filipowicz, Bogusław; Kwiecień, Joanna
Advertisement as a one of marketing elements absorbs part of firms budget. Measuring the advertisement effectiveness as regards its range and noticeability is very essential. This article presents methods, which could be successfully applied to modeling of advertisement effectiveness. The modeling of press advertisement effectiveness depending on number of running and pace of range's drop in the case of advertisement repeats is also presented.
Access status: Open Access ,
New genetic algorithm based on dissimilarities and similarities
(Wydawnictwa AGH, 2018) Al-Jawadi, Radhwan; Studniarski, Marcin; Younus, Aisha
Optimization is essential for nding suitable answers to real life problems. In particular, genetic (or more generally, evolutionary) algorithms can provide satisfactory approximate solutions to many problems to which exact analytcal results are not accessible. In this paper we present both theoretical and experimental results on a new genetic algorithm called Dissimilarity and Simlarity of Chromosomes (DSC). This methodology constructs new chromosomes starting with the pairs of existing ones by exploring their dissimilarities and similarities. To demonstrate the performance of the algorithm, it is run on 17 two-dimensional, one four-dimensional and two ten-dimensional optimization problems described in the literature, and compared with the well-known GA, CMA-ES and DE algorithms. The results of tests show the superiority of our strategy in the majority of cases.
Access status: Restricted ,
Optymalizacja giełdowej strategii inwestycyjnej za pomocą algorytmu genetycznego
(Data obrony: 2019-01-21) Domarecki, Sebastian
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Open Access ,
Przedstawienie wyników działania algorytmu genetycznego dla zadania CLSP planowania wielkości i szeregowania partii produkcyjnej
(Wydawnictwa AGH, 2011) Książek, Roger
This paper presents the results obtained using a genetic algorithm to solve mixed integer programming task for the capacitated lot sizing problem. CLSP model was chosen from among many models with different variants of this problem as a basic for development of genetic algorithm. In this paper is summarized a comparison between the results of a genetic algorithm with the results of mixed integer programming for solving the same problem.
Access status: Open Access ,
The advent of the deep learning evolutionary algorithm EvoDN2 and its recent applications
(Wydawnictwa AGH, 2025) Chakraborti, Nirupam
The evolutionary deep learning algorithm EvoDN2 is an emerging strategy for data-driven intelligent learning and many-objective optimisation capable of handling a large volume of noisy and non-linear data. This article provides the essential details of this algorithm and highlights a number of its recent applications.
Access status: Open Access ,
The application of genetic algorithms for the selection of WSE companies in warsaw for an investment portfolio
(AGH University of Science and Technology Press, 2020) Basiura, Beata; Motyczyńska, Joanna
Portfolio analysis is a tool in particular, intended for investors. Risk assessment and risk specification make the investor able to diversify properly and offset the portfolio. Broadly speaking, there are multiple tools designed to create an efficient set of portfolios. One of them is Markowitz's model theory, postulating building up a portfolio to determine the basis of equilibrium between expected profit level as well as accepted level of risk assessment. In the context of this paper, the objective is to shed some light on creating investment portfolios based on either Markowitz's portfolio theory or an evolutionary algorithm. The simulation based methods for building up a portfolio of approximately 40-50 companies listed on the primary market of the Warsaw Stock Exchange using the specific selection function are presented. Portfolio profit values have been evaluated in a dynamically shifted time window. The conducted analysis showed shifts in the economy at certain periods of time. The implemented genetic algorithms smoothly handled the optimization with a relatively short processing time of the task result.
Access status: Restricted ,
Zastosowanie algorytmu przybliżonego w znajdowaniu połączeń komunikacyjnych
(Data obrony: 2017-01-31) Ogrodnik, Łukasz
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej