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Tytuł:
Evolutionary algorithm with a configurable search mechanism
Autorzy:
Łapa, Krystian
Cpałka, Krzysztof
Laskowski, Łukasz
Cader, Andrzej
Zeng, Zhigang
Powiązania:
https://bibliotekanauki.pl/articles/1837536.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
evolutionary algorithm
population-based algorithm
optimization
operator pool
operator selection
individual selection
Opis:
In this paper, we propose a new population-based evolutionary algorithm that automatically configures the used search mechanism during its operation, which consists in choosing for each individual of the population a single evolutionary operator from the pool. The pool of operators comes from various evolutionary algorithms. With this idea, a flexible balance between exploration and exploitation of the problem domain can be achieved. The approach proposed in this paper might offer an inspirational alternative in creating evolutionary algorithms and their modifications. Moreover, different strategies for mutating those parts of individuals that encode the used search operators are also taken into account. The effectiveness of the proposed algorithm has been tested using typical benchmarks used to test evolutionary algorithms.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 151-171
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An evolutionary algorithm determining a defuzzyfication functional
Autorzy:
Kosiński, W.
Markowska-Kaczmar, U.
Powiązania:
https://bibliotekanauki.pl/articles/1943273.pdf
Data publikacji:
2007
Wydawca:
Politechnika Gdańska
Tematy:
ordered fuzzy numbers
defuzzyfication
genetic algorithm
Opis:
Order fuzzy numbers are defined that make it possible to deal with fuzzy inputs quantitatively, exactly in the same way as with real numbers, together with four algebraic operations. An approximation formula is given for a defuzzyfication functional that plays the main role when dealing with fuzzy controllers and fuzzy inference systems. A dedicated evolutionary algorithm is presented in order to determine the form of a functional when a training set is given. The form of a genotype composed of three types of chromosomes and the fitness function are given and Genetic operators are proposed.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2007, 11, 1-2; 47-58
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary algorithm for learning Bayesian structures from data
Autorzy:
Kozłowski, M.
Wierzchoń, S. T.
Powiązania:
https://bibliotekanauki.pl/articles/1986916.pdf
Data publikacji:
2002
Wydawca:
Politechnika Gdańska
Tematy:
Bayesian networks
structure learning
evolutionary algorithm
discrete optimization
Opis:
In this paper we report an evolutionary approach to learning Bayesian networks from data. We explain reasons, which advocate such a non-deterministic approach. We analyze weaknesses of previous works and come to conclusion that we should operate in the search space native for the problem i.e. in the space of directed acyclic graphs instead of standard space of binary strings. This requires adaptation of evolutionary methodology into very specific needs. We propose quite new data representation and implementation of generalized genetic operators and then we present an efficient algorithm capable of learning complex networks without additional assumptions. We discuss results obtained with this algorithm. The approach presented in this paper can be extended with the possibility to absorb some suggestions from experts or obtained by means of data preprocessing.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2002, 6, 3; 509-521
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Learning decision rules using a distributed evolutionary algorithm
Autorzy:
Kwedlo, W.
Krętowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/1986918.pdf
Data publikacji:
2002
Wydawca:
Politechnika Gdańska
Tematy:
decision rule learning
distributed evolutionary algorithms
Opis:
A new parallel method for learning decision rules from databases by using an evolutionary algorithm is proposed. We describe an implementation of EDRL-MD system in the cluster of multiprocessor machines connected by Fast Ethernet. Our approach consists in a distribution of the learning set into processors of the cluster. The evolutionary algorithm uses a master-slave model to compute the fitness function in parallel. The remiander of evolutionary algorithm is executed in the master node. The experimental results show, that for large datasets our approach is able to obtain a significant speed-up in comparison to a single processor version.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2002, 6, 3; 483-492
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary algorithm for selecting dynamic signatures partitioning approach
Autorzy:
Zalasiński, Marcin
Laskowski, Łukasz
Niksa-Rynkiewicz, Tacjana
Cpałka, Krzysztof
Byrski, Aleksander
Przybyszewski, Krzysztof
Trippner, Paweł
Dong, Shi
Powiązania:
https://bibliotekanauki.pl/articles/2147146.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
identity verification
dynamic signature
hybrid partitions
partitions’ selection
evolutionary algorithm
Opis:
In the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared. In this paper, we propose an approach that: (a) uses an evolutionary algorithm to create signature partitions in the time and velocity domains; (b) selects the most characteristic partitions in terms of matching with reference signatures; and (c) works individually for each user, eliminating the need of using skilled forgeries. The proposed approach was tested using Biosecure DS2 database which is a part of the DeepSignDB, a database with genuine dynamic signatures. Our simulations confirmed the correctness of the adopted assumptions.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 267--279
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary algorithm for minmax regret flow-shop problem
Autorzy:
Ćwik, M.
Józefczyk, J.
Powiązania:
https://bibliotekanauki.pl/articles/406859.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
manufacturing
flow-shop
interval uncertainty
min-max regret
heuristic algorithms
evolutionary algorithms
simulation
Opis:
The uncertain flow-shop is considered. It is assumed that processing times are not given a priori, but they belong to intervals of known bounds. The absolute regret (regret) is used to evaluate a solution (a schedule) which gives the minmax regret binary optimization problem. The evolutionary heuristic solution algorithm is experimentally compared with a simple middle interval heuristic algorithm for three machines instances. The conducted simulations confirmed the several percent advantage of the evolutionary approach.
Źródło:
Management and Production Engineering Review; 2015, 6, 3; 3-9
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary Algorithm that Designs the DNA Synthesis Procedure
Autorzy:
Michalak, M.
Nowak, R.
Powiązania:
https://bibliotekanauki.pl/articles/308431.pdf
Data publikacji:
2011
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
bioinformatics
gene synthesis
optimum searching
Opis:
Chemical synthesis of nucleotide chains is very erroneous for long sequences. Often a gene is constructed from short fragments joined with the use of complementary helper chains. The number of possible potential solutions for a long gene synthesis is very large, therefore a fast automated search is required. In the presented approach a modified method of long DNA construction is proposed. A computer program that searches for an optimal solution in the space of potential synthesis methods has been developed. This software uses an evolutionary algorithm for global optimization and a hillclimbing algorithm for local optimization. The long DNA construction method was tested on random sequences. The results are very promising. The next step is to perform experiments in a biotechnological wet laboratory involving DNA strand synthesis using the method designed by the presented software.
Źródło:
Journal of Telecommunications and Information Technology; 2011, 4; 50-54
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Distributed Evolutionary Algorithm for Path Planning in Navigation Situation
Autorzy:
Śmierzchalski, R.
Kuczkowski, Ł.
Kolendo, P.
Jaworski, B.
Powiązania:
https://bibliotekanauki.pl/articles/116175.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
evolutionary algorithm
path planning
simulation environment
Opis:
This article presents the use of a multi‐population distributed evolutionary algorithm for path planning in navigation situation. The algorithm used is with partially exchanged population and migration between independently evolving populations. In this paper a comparison between a multi‐population and a classic single‐population algorithm takes place. The impact on the ultimate solution has been researched. It was shown that using several independent populations leads to an improvement of the ultimate solution compared to a single population approach. The concept was checked against a problem of maritime collision avoidance.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2013, 7, 2; 293-300
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Solving the problem of vehicle routing by evolutionary algorithm
Autorzy:
Iwańkowicz, R. R.
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/102797.pdf
Data publikacji:
2016
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
vehicle routing
travelling salesman
genetic algorithm
Opis:
In the presented work the vehicle routing problem is formulated, which concerns planning the collection of wastes by one garbage truck from a certain number of collection points. The garbage truck begins its route in the base point, collects the load in subsequent collection points, then drives the wastes to the disposal site (landfill or sorting plant) and returns to the another visited collection points. The filled garbage truck each time goes to the disposal site. It returns to the base after driving wastes from all collection points. Optimization model is based on genetic algorithm where individual is the whole garbage collection plan. Permutation is proposed as the code of the individual.
Źródło:
Advances in Science and Technology. Research Journal; 2016, 10, 29; 97-108
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simultaneous optimization of flotation column performance using genetic evolutionary algorithm
Autorzy:
Nakhaei, F.
Irannajad, M.
Yousefikhoshbakht, M.
Powiązania:
https://bibliotekanauki.pl/articles/110806.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
flotation column
optimization
genetic algorithm
non-linear regression
upgrading curve
Opis:
Column flotation is a multivariable process. Its optimization guarantees the metallurgical yield of the process, expressed by the grade and recovery of the concentrate. The present work aimed at applying genetic algorithms (GAs) to optimize a pilot column flotation process which is characterized by being difficult to be optimized via conventional methods. A non-linear mathematical model was used to describe the dynamic behavior of the multivariable process. The solution of the optimization problem using conventional algorithms does not always lead to convergence because of the high dimensionality and non-linearity of the model. In order to deal with this process, the use of a genetic evolutionary algorithm is justified. In this way, GA was coupled with the multivariate non-linear regression (MNLR) of the column flotation metallurgical performance as a fitting function in order to optimize the column flotation process. Then, this kind of intelligent approach was verified by using mineral processing approaches such as Halbich’s upgrading curve. The aim of the optimization through GAs was searching for the process inputs that maximize the productivity of copper in the Sarcheshmeh pilot plant. In this case, the simulation optimization problem was defined as finding the best values for the froth height, chemical reagent dosage, wash water, air flow rate, air holdup, and Cu grade in rougher and column feed streams. The results indicated that GA was a robust and powerful search method to find the best values of the flotation column model parameters that lead to more reliable simulation predictions at a reasonable time. Based on the grade–recovery Halbich upgrading curve, the MNLR model coupled with GA can be used for determination of the flotation optimum conditions.
Źródło:
Physicochemical Problems of Mineral Processing; 2016, 52, 2; 874-893
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of modification of the evolutionary algorithm for sequencing production tasks
Autorzy:
Ciepliński, Piotr
Golak, Sławomir
Wieczorek, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/29520067.pdf
Data publikacji:
2022
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
evolutionary algorithm
task sequencing
mutation operator
algorytm ewolucyjny
operator mutacji
Opis:
Evolutionary algorithms are one of the heuristic techniques used to solve task sequencing problems. An important example of such a problem is the issue of sequencing production tasks. The combinatorial optimization of task sequences allows the minimization of the cost or time of a set of production tasks by reducing the components of these values which are present in the transitions between tasks. This paper aims to analyze the influence of the production nature expressed by a set of production task parameters and a definition of the task transition cost on the effectiveness of the modification of the evolutionary algorithm based on new directed stochastic mutation operators. The research carried out included the influence of the space dimension of the task parameters, the number of levels of the value of the cost function, and a definition of this function. The results obtained allow us to assess the effectiveness of the directed mutation in task sequencing for productions of various natures.
Źródło:
Computer Methods in Materials Science; 2022, 22, 3; 157-166
2720-4081
2720-3948
Pojawia się w:
Computer Methods in Materials Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid evolutionary algorithm of optimized controller placement in SDN environment
Autorzy:
Hemagowri, J.
Tamil Selvan, P.
Powiązania:
https://bibliotekanauki.pl/articles/38704829.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
controller
software defined network
Gaussian chaotic map
fish swarm
multi-criteria optimization
kontroler
sieć zdefiniowana programowo
mapa chaosu Gaussa
rój ryb
optymalizacja wielokryterialna
Opis:
Controller placement problem (CPP) is a significant technological challenge in software defined network (SDN). Deployment of a properly designed SDN-based network is required to detect optimal number of controllers for enhancing the network’s performance. However, the best possible controller placement for enhancing the network’s performance faces many issues. To solve the CPP, a novel technique called the hybrid evolutionary algorithm of optimized controller placement (HEA-OCP) in SDN environment is introduced to increase network’s performance by different network topologies. In the proposed model, optimized controller placement using improved multi-objective artificial fish optimization is employed to improve data transmission and reduce latency. Controller placement can be determined using an undirected graph based on a variety of factors, including propagation delay, load balancing capabilities and bandwidth, fault tolerance and data transfer rate, and a variety of other factors. For each controller, the fitness value is calculated over multi-criteria functions. The optimizer’s performance can be improved with the use of Gaussian chaotic maps. In large-scale SDN networks using HEC-OCP, the algorithm dynamically analyzes the optimal number of controllers and the best connections between switches and controllers. As a result, the overall network performance is improved and the delay minimization-based controller placement strategy is obtained. The simulation of HEA-OCP with existing methods is conducted by a network topology dataset of various metrics, namely packet delivery ratio, packet drop rate, throughput, average latency, and jitter. The proposed HEA-OCP improves the packet delivery and throughput with reduced average latency, and packet drop ensures more instantaneous communications in real-time applications of SDN for better decision-making.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 4; 539-556
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of vehicle routing problem using evolutionary algorithm with memory
Autorzy:
Podlaski, K.
Wiatrowski, G.
Powiązania:
https://bibliotekanauki.pl/articles/305266.pdf
Data publikacji:
2017
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
vehicle routing problem
time windows
evolutionary algorithms
multi-objective optimization
Opis:
The idea of a new evolutionary algorithm with memory aspect included is proposed to find multiobjective optimized solution of vehicle routing problem with time windows. This algorithm uses population of agents that individually search for optimal solutions. The agent memory incorporates the process of learning from the experience of each individual agent as well as from the experience of the population. This algorithm uses crossover operation to define agents evolution. In the paper we choose as a base the Best Cost Route Crossover (BCRC) operator. This operator is well suited for VPRTW problems. However it does not treat both of parent symmetrically what is not natural for general evolutionary processes. The part of the paper is devoted to find an extension of the BCRC operator in order to improve inheritance of chromosomes from both of parents. Thus, the proposed evolutionary algorithm is implemented with use of two crossover operators: BCRC and its extended-modified version. We analyze the results obtained from both versions applied to Solomon’s and Gehring & Homberger instances. We conclude that the proposed method with modified version of BCRC operator gives statistically better results than those obtained using original BCRC. It seems that evolutionary algorithm with memory and modification of Best Cost Route Crossover Operator lead to very promising results when compared to the ones presented in the literature.
Źródło:
Computer Science; 2017, 18 (3); 269-286
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reactive distillation for multiple-reaction systems: optimisation study using an evolutionary algorithm
Autorzy:
Keller, T.
Dreisewerd, B.
Górak, A.
Powiązania:
https://bibliotekanauki.pl/articles/185082.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
nonequilibrium-stage model
Pareto front
multi-objective optimization
diethyl
carbonate
ethyl methyl carbonate
model równowagi
optymalizacja wielokryterialna
dietyl
węglan
etylo-węglan metylu
Opis:
Reactive distillation (RD) has already demonstrated its potential to significantly increase reactant conversion and the purity of the target product. Our work focuses on the application of RD to reaction systems that feature more than one main reaction. In such multiple-reaction systems, the application of RD would enhance not only the reactant conversion but also the selectivity of the target product. The potential of RD to improve the product selectivity of multiple reaction systems has not yet been fully exploited because of a shortage of available comprehensive experimental and theoretical studies. In the present article, we want to theoretically identify the full potential of RD technology in multiple-reaction systems by performing a detailed optimisation study. An evolutionary algorithm was applied and the obtained results were compared with those of a conventional stirred tank reactor to quantify the potential of RD to improve the target product selectivity of multiple-reaction systems. The consecutive transesterification of dimethyl carbonate with ethanol to form ethyl methyl carbonate and diethyl carbonate was used as a case study.
Źródło:
Chemical and Process Engineering; 2013, 34, 1; 17-38
0208-6425
2300-1925
Pojawia się w:
Chemical and Process Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Implementing evolutionary algorithm into training single-layer artificial neural network in classification task
Autorzy:
Płaczek, S.
Powiązania:
https://bibliotekanauki.pl/articles/95001.pdf
Data publikacji:
2016
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
genetic algorithm
evolutionary algorithm
selection process
mutation
recombination
replacement
Opis:
The article proposes implementing a modified version of genetic algorithm in a neural network, what in literature is known as “evolutionary algorithm” or “evolutionary programming”. An Evolutionary Algorithm is a probabilistic algorithm that works in a set of weight variability of neurons and seeks the optimal value solution within a population of individuals, avoiding the local maximum. For chromosomes the real value variables and matrix structure are proposed to a single-layer neural network. Particular emphasis is put on mutation and crossover algorithms. What is also important in both genetic and evolutionary algorithms is the selection process. In the calculation example, the implementation of theoretical considerations to a classification task is demonstrated.
Źródło:
Information Systems in Management; 2016, 5, 3; 377-388
2084-5537
2544-1728
Pojawia się w:
Information Systems in Management
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Tunning parameters of evolutionary algorithm in Travelling Salesman Problem with profits and returns
Autorzy:
Koszelew, J.
Piwońska, A.
Powiązania:
https://bibliotekanauki.pl/articles/393341.pdf
Data publikacji:
2010
Wydawca:
Polskie Stowarzyszenie Telematyki Transportu
Tematy:
sieć transportowa
TSP
algorytm ewolucyjny
routing in transport networks
travelling salesman problem with profits
evolutionary algorithm
Opis:
A huge number of papers studies Travelling Salesman Problem (TSP) in classical version. In standard TSP all cities must be visited and graph is completed. While this is indeed the case in many practical problems, there are many other practical problems where these assumptions are not valid. This paper presents a new evolutionary algorithm (EA) which solves TSP with profits and returns (TSPwPR). This version of TSP is often applied in Intelligent Transport Systems, especially in Vehicle Routing Problem (VRP). TSPwPR consists in finding a cycle which maximizes collected profit but does not exceed a given cost constraint. A graph which is considered in this problem can be not completed, salesman doesn't have to visit all cities and he can repeat (with zero profit) cities in his tour. The method was implemented and tested on real network which consists of 160 cities in eastern and central voivodeships of Poland. The main parameter which has the highest influence on quality of obtaining results is the size of population and our experiments are directed to determine an optimal value of this parameter.
Źródło:
Archives of Transport System Telematics; 2010, 3, 1; 17-22
1899-8208
Pojawia się w:
Archives of Transport System Telematics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Self-configuring hybrid evolutionary algorithm for fuzzy imbalanced classification with adaptive instance selection
Autorzy:
Stanovov, V.
Semenkin, E.
Semenkina, O.
Powiązania:
https://bibliotekanauki.pl/articles/91578.pdf
Data publikacji:
2016
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
fuzzy classification
instance selection
genetic fuzzy system
self-configuration
Opis:
A novel approach for instance selection in classification problems is presented. This adaptive instance selection is designed to simultaneously decrease the amount of computation resources required and increase the classification quality achieved. The approach generates new training samples during the evolutionary process and changes the training set for the algorithm. The instance selection is guided by means of changing probabilities, so that the algorithm concentrates on problematic examples which are difficult to classify. The hybrid fuzzy classification algorithm with a self-configuration procedure is used as a problem solver. The classification quality is tested upon 9 problem data sets from the KEEL repository. A special balancing strategy is used in the instance selection approach to improve the classification quality on imbalanced datasets. The results prove the usefulness of the proposed approach as compared with other classification methods.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 3; 173-188
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of Evolutionary Algorithm and Heuristics for Flow Optimization in P2P Systems
Autorzy:
Kucharzak, M.
Siwek, A.
Walkowiak, K.
Powiązania:
https://bibliotekanauki.pl/articles/226952.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
P2P
flows
network optimization
Opis:
Nowadays, many Internet users make use of Peer-to-Peer (P2P) systems to download electronic content including music, movies, software, etc. Growing popularity in P2P based protocol implementations for file sharing purposes caused that the P2P traffic exceeds Web traffic and in accordance with to many statistics, P2P systems produce a more than 50% of the whole Internet traffic. Therefore, P2P systems provide remarkable income for Internet Service Providers (ISP). However, at the same time P2P systems generates many problems related to traffic engineering, optimization, network congestion. In this paper we focus on the problem of flow optimization in P2P file sharing systems. Corresponding to BitTorrent-based systems behaviour, the optimization of P2P flows is very complex and in this work we consider different heuristic strategies for content distribution and moreover we propose a new evolutionary algorithm (EA) for this problem. We compare results of the algorithms against optimal results yielded by CPLEX solver for networks including 10 peers and relation to random algorithm for 100-node systems. According to numerical experiments, the EA provides solutions close to optimal for small instances and all of the heuristics exhibit a superior performance over random search.
Źródło:
International Journal of Electronics and Telecommunications; 2010, 56, 2; 145-152
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Parameters tuning of evolutionary algorithm for the orienteering problem
Kalibracja parametrów algorytmu ewolucyjnego rozwiązującego Orienteering Problem
Autorzy:
Ostrowski, K.
Powiązania:
https://bibliotekanauki.pl/articles/88372.pdf
Data publikacji:
2015
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
kalibracja parametrów
algorytmy ewolucyjne
Orienteering Problem
parameter tuning
evolutionary algorithms
Opis:
Various classes of algorithms solving optimization problems have some set of parameters. Setting them to appropriate values can be as important to results quality as choosing right algorithm components. Parameter calibration can be a complex optimization problem itself and many meta-algorithms were proposed to deal with it in a more automatic way. This paper presents automatic parameter tuning of an evolutionary algorithm solving the Orienteering Problem. ParamsILS method was chosen as a tuner. Obtained results show the importance of appropriate parameter setting in evolutionary algorithms: tuned algorithm achieved very high-quality solutions on known Orienteering Problem benchmarks.
Różne klasy algorytmów rozwiązujących problemy optymalizacyjne posiadają zestawy parametrów. Ustawienie odpowiednich wartości parametrów może być równie ważne, co dobór odpowiednich komponentów algorytmu. Kalibracja parametrów sama w sobie może być skomplikowanym problemem optymalizacyjnym i wiele meta-algorytmów zostało zaproponowanych by przeprowadzać ten proces automatycznie. Artykuł prezentuje automatyczną kalibrację parametrów algorytmu ewolucyjnego rozwiązującego Orienteering Problem. W tym celu wybrano metodę ParamsILS. Otrzymane rezultaty ukazują jak ważny jest odpowiedni dobór parametrów: algorytm po kalibracji uzyskał bardzo wysokiej jakości rozwiązania dla znanych sieci testowych.
Źródło:
Advances in Computer Science Research; 2015, 12; 53-78
2300-715X
Pojawia się w:
Advances in Computer Science Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sterowanie pracą hydroelektrowni z wykorzystaniem algorytmu ewolucyjnego
Controlling a hydropower plant with use of evolutionary algorithm
Autorzy:
Gajer, M.
Powiązania:
https://bibliotekanauki.pl/articles/151237.pdf
Data publikacji:
2011
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
systemy ewolucyjne
systemy elektroenergetyczne
hydroelektrownie
optymalizacja
evolutionary systems
energetic systems
hydropower plants
optimization
Opis:
W artykule rozważono możliwość wykorzystania techniki obliczeniowej opartej na zastosowaniu algorytmów ewolucyjnych w celu optymalizacji pracy elektrowni wodnej. Założono, że rozważana elektrownia wodna, oprócz stałego dopływu wody z rzeki, dodatkowo wyposażona jest również w człony pompowe, za pomocą których można w okresie niskiego zapotrzebowania na energię elektryczną tłoczyć wodę ze zbiornika retencyjnego do zbiornika głównego elektrowni, gromadząc w ten sposób energię potencjalną mas wodnych, którą można następnie wykorzystać do produkcji energii elektrycznej w okresie występowania szczytu zapotrzebowania, czyli wtedy, gdy koszty wytworzenia energii w klasycznych elektrowniach cieplnych są relatywnie najwyższe. Przedstawione w artykule wyniki symulacji komputerowych wskazują, że algorytmy ewolucyjne można z powodzeniem wykorzystać do realizacji rozważanego zagadnienia optymalizacyjnego, dzięki czemu są w stanie zagwarantować odpowiednio niskie dobowe koszty produkcji energii elektrycznej przy jednoczesnym spełnieniu wszelkich koniecznych ograniczeń nałożonych na pracę systemu elektroenergetycznego. Dodatkowo gwarantują one zbilansowanie zbiornika elektrowni wodnej w dobowym przedziale czasowym.
The paper discusses implementation of a computational technique based on evolutionary algorithms for the purpose of optimisation of hydropower plant work. There is assumed that a hydropower plant is situated on a river that delivers water into a reservoir. The hydropower plant is additionally equipped with pumping units by means of which the water can be stored in the main reservoir during the periods of low power demand. In the next stage, the potential energy of the pumped water can be converted again into electrical energy during the periods of high power demand. The fitness function for the evolutionary algorithm is defined by the equation (5) and it takes into account the cost of burnt fuel, the balance of power in the energetic system, and the balance of water in the reservoir. The paper is divided into four sections. Section 1 is short introduction to the problems of energetic system optimisation. Section 2 describes in detail the energetic system to be optimised. The system is composed of one large thermal power unit and one hydropower plant with pumping units. The changes of power demand in the energetic system are presented in Table 1; Table 2 provides the parameters of the thermal unit. In Section 3 there are given the results of numerical experiments obtained by use of the evolutionary algorithm. Figure 1 shows the plot of power changes of the thermal unit. It can be noted that the thermal unit power for most time is as low as possible, which guarantees low cost of burnt fuel. The thermal unit power grows only during the period of high power demand in order to fulfill the balance of power in the energetic system. Figure 2 is a diagram illustrating the mode of the hydropower plant operation. It can be noted that the hydropower plant operates in the pumping mode only during the hours of the lowest power demand. The results of computer simulations presented in the paper show that evolutionary algorithms can be effectively used for solving the optimisation task for energetic systems. Moreover, evolutionary algorithms can guarantee low cost of pro-duction of electrical energy, when simultaneously meeting all the constraints connected with necessity of balancing the power in the energetic system and balancing the amount of water in the hydropower plant reservoir.
Źródło:
Pomiary Automatyka Kontrola; 2011, R. 57, nr 2, 2; 193-196
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie algorytmu genetycznego do optymalizacji konstrukcji pasywnej przekładni magnetycznej
Optimization of magnetic gear using evolutionary algorithm
Autorzy:
Kowol, M.
Kołodziej, J.
Łukaniszyn, M.
Powiązania:
https://bibliotekanauki.pl/articles/377758.pdf
Data publikacji:
2016
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
przekładnia magnetyczna
metoda elementów skończonych
algorytm ewolucyjny
Opis:
W pracy przedstawiono wpływ wybranych parametrów konstrukcyjnych pasywnej przekładni magnetycznej na gęstość przenoszonego momentu. Na tej podstawie określono liczbę parametrów konstrukcyjnych oraz ich przedziały zmienności w procesie optymalizacyjnym. Obliczenia wykonano za pomocą dwuwymiarowej metody elementów skończonych, zaimplementowanej w środowisku Matlab. W wyniku przeprowadzonej optymalizacji otrzymano parametry konstrukcyjne przekładni magnetycznej o znacznie większej wartości przenoszonego momentu.
The paper presents the influence of selected design parameters of passive magnetic gear on the transmitted torque density. On this basis, the number of design parameters and their ranges of variation, in the optimization process were obtained. Calculations were performed using a two-dimensional finite element method implemented in Matlab. As a result of optimization authors have obtained the design parameters of magnetic gear with a much higher value of the transmitted torque density.
Źródło:
Poznan University of Technology Academic Journals. Electrical Engineering; 2016, 85; 423-432
1897-0737
Pojawia się w:
Poznan University of Technology Academic Journals. Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal control of multistage deterministic, stochastic and fuzzy processes in the fuzzy environment via an evolutionary algorithm
Autorzy:
Stańczak, J.
Powiązania:
https://bibliotekanauki.pl/articles/970100.pdf
Data publikacji:
2005
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
sterowanie rozmyte
adaptacyjny algorytm ewolucyjny
fuzzy control
multistage optimal fuzzy control
adaptive evolutionary algorithm
Opis:
This paper deals with the problem of control of deterministic, stochastic and fuzzy systems with a fixed termination time and fuzzy constraints imposed on controls and states. Constrains imposed on the system are given as membership functions of particular fuzzy sets. Transition functions for controlled systems are given as a matrix of transitions between states for a deterministic object, a matrix of probabilities of transitions for a stochastic object and a matrix of membership functions of transitions for a fuzzy system. An optimal (or sub-optimal) control is obtained using a specialized evolutionary algorithm (EA), which is a development over the previously used methods based on simple genetic algorithm. The specialized EA seems to be a very effective tool for solving such a class of optimization problems, comparing advantageously with the traditional simple genetic algorithm approach and with the previously used solutions like dynamic programming or branch and bound. The specialization of the applied EA is obtained using dedicated problem encoding, the method of ranking of genetic operators and the controlled selection of population members.
Źródło:
Control and Cybernetics; 2005, 34, 2; 525-552
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Selection of control parameters in a control system with a DC electric series motor using evolutionary algorithm
Autorzy:
Hudy, W.
Jaracz, K.
Powiązania:
https://bibliotekanauki.pl/articles/141057.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
algorytm ewolucyjny
optymalizacja parametryczna
silnik elektryczny
evolutionary algorithm
parametric optimization
DC electric series motor
Opis:
This paper presents a method of selection of regulator parameters in a control system using evolutionary algorithm. The control system has one PI controller and one hysteresis controller. The value of the proportional band and the value of the Integral time were defined by evolutionary algorithms. The object of control was a Brown Boveri GS10A motor. The task functions were the step change of rotational speed and step change of the motor's torque. The control system with the parameters selected by means of the evolutionary method was verified by using MATLAB/Simulink environment.
Źródło:
Archives of Electrical Engineering; 2011, 60, 3; 231-237
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mining Pharmacy Database Using Evolutionary Genetic Algorithm
Autorzy:
Ykhlef, M.
ElGibreen, H.
Powiązania:
https://bibliotekanauki.pl/articles/226717.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
data mining
evolutionary algorithms
genetic algorithm
pharmacy database
sequential patterns
Opis:
Medication management is an important process in pharmacy field. Prescribing errors occur upstream in the process, and their effects can be perpetuated in subsequent steps. Prescription errors are an important issue for which conflicts with another prescribed medicine could cause severe harm for a patient. In addition, due to the shortage of pharmacists and to contain the cost of healthcare delivery, time is also an important issue. Former knowledge of prescriptions can reduce the errors, and discovery of such knowledge requires data mining techniques, such as Sequential Pattern. Moreover, Evolutionary Algorithms, such as Genetic Algorithm (GA), can find good rules in short time, thus it can be used to discover the Sequential Patterns in Pharmacy Database. In this paper GA is used to assess patient prescriptions based on former knowledge of series of prescriptions in order to extract sequenced patterns and predict unusual activities to reduce errors in timely manner.
Źródło:
International Journal of Electronics and Telecommunications; 2010, 56, 4; 427-432
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minimizing makespan in general flow-shop scheduling problem using a GA-based improvement heuristic
Autorzy:
Semančo, P.
Powiązania:
https://bibliotekanauki.pl/articles/117960.pdf
Data publikacji:
2011
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
flow-shop production
evolutionary algorithm
Opis:
In the paper an improvement heuristic is proposed for permutation flow-shop problem based on the idea of evolutionary algorithm. The approach employs constructive heuristic that gives a good initial solution. GA-based improvement heuristic is applied in conjunction with three well-known constructive heuristics, namely CDS, Gupta’s algorithm and Palmer’s Slope Index. The approach is tested on benchmark set of 10 problems range from 4 to 25 jobs and 4 to 30 machines. The results are also compared to the best-known lower-bound solutions.
Źródło:
Applied Computer Science; 2011, 7, 1; 57-64
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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