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Tytuł:
A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:
Knypiński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:
The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of daily operations in the marine industry using ant colony optimization (ACO)-An artificial intelligence (AI) approach
Autorzy:
Sardar, A.
Anantharaman, M.
Garaniya, V.
Khan, F.
Powiązania:
https://bibliotekanauki.pl/articles/24201433.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
ant colony optimization
artificial intelligence
maritime transport
International Maritime Organization
international safety management
formal safety assessment
algorithms
Opis:
The maritime industry plays a crucial role in the global economy, with roughly 90% of world trade being conducted through the use of merchant ships and more than a million seafarers. Despite recent efforts to improve reliability and ship structure, the heavy dependence on human performance has led to a high number of casualties in the industry. Decision errors are the primary cause of maritime accidents, with factors such as lack of situational awareness and attention deficit contributing to these errors. To address this issue, the study proposes an Ant Colony Optimization (ACO) based algorithm to design and validate a verified set of instructions for performing each daily operational task in a standardised manner. This AI-based approach can optimise the path for complex tasks, provide clear and sequential instructions, improve efficiency, and reduce the likelihood of human error by minimising personal preference and false assumptions. The proposed solution can be transformed into a globally accessible, standardised instructions manual, which can significantly contribute to minimising human error during daily operational tasks on ships.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 290--295
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of Job Shop Scheduling Problem by Genetic Algorithms: Case Study
Autorzy:
Sahar, Habbadi
Herrou, Brahim
Sekkat, Souhail
Powiązania:
https://bibliotekanauki.pl/articles/24200523.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
optimization
metaheuristics
scheduling
job shop scheduling problem
genetic algorithms
simulation
Opis:
The Job Shop scheduling problem is widely used in industry and has been the subject of study by several researchers with the aim of optimizing work sequences. This case study provides an overview of genetic algorithms, which have great potential for solving this type of combinatorial problem. The method will be applied manually during this study to understand the procedure and process of executing programs based on genetic algorithms. This problem requires strong decision analysis throughout the process due to the numerous choices and allocations of jobs to machines at specific times, in a specific order, and over a given duration. This operation is carried out at the operational level, and research must find an intelligent method to identify the best and most optimal combination. This article presents genetic algorithms in detail to explain their usage and to understand the compilation method of an intelligent program based on genetic algorithms. By the end of the article, the genetic algorithm method will have proven its performance in the search for the optimal solution to achieve the most optimal job sequence scenario.
Źródło:
Management and Production Engineering Review; 2023, 14, 3; 44--56
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Shape optimization of the muffler shield with regard to strength properties
Autorzy:
Jarosz, Joachim
Długosz, Adam
Powiązania:
https://bibliotekanauki.pl/articles/38903721.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
muffler shield
evolutionary algorithms
multi-objective optimization
finite element method
optimal design
Opis:
This paper is devoted to the shape optimization of the muffler shield with regard to strength properties. Three different optimization criteria are defined and numerically implemented concerning the strength properties of the shield, and different variants of optimization tasks are solved using both built-in optimization modules and in-house external algorithms. The effectiveness and efficiency of the optimization methods used are compared and presented.
Źródło:
Engineering Transactions; 2023, 71, 3; 351-366
0867-888X
Pojawia się w:
Engineering Transactions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applying optimization techniques on cold-formed C-channel section under bending
Autorzy:
El-Lafy, Heba F.
Elgendi, Elbadr O.
Morsy, Alaa M.
Powiązania:
https://bibliotekanauki.pl/articles/27312402.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
kształtownik zimnogięty
optymalizacja
algorytm genetyczny
cold-formed sections
single optimization
multi-objective optimization
genetic algorithms
effective width method
C-channel beams
Opis:
There are no standard dimensions or shapes for cold-formed sections (CFS), making it difficult for a designer to choose the optimal section dimensions in order to obtain the most cost-effective section. A great number of researchers have utilized various optimization strategies in order to obtain the optimal section dimensions. Multi-objective optimization of CFS C-channel beams using a non-dominated sorting genetic algorithm II was performed using a Microsoft Excel macro to determine the optimal cross-section dimensions. The beam was optimized according to its flexural capacity and cross-sectional area. The flexural capacity was computed utilizing the effective width method (EWM) in accordance with the Egyptian code. The constraints were selected so that the optimal dimensions derived from optimization would be production and construction-friendly. A Pareto optimal solution was obtained for 91 sections. The Pareto curve demonstrates that the solution possesses both diversity and convergence in the objective space. The solution demonstrates that there is no optimal solution between 1 and 1.5 millimeters in thickness. The solutions were validated by conducting a comprehensive parametric analysis of the change in section dimensions and the corresponding local buckling capacity. In addition, performing a single-objective optimization based on section flexural capacity at various thicknesses The parametric analysis and single optimization indicate that increasing the dimensions of the elements, excluding the lip depth, will increase the section’s carrying capacity. However, this increase will depend on the coil’s wall thickness. The increase is more rapid in thicker coils than in thinner ones.
Źródło:
International Journal of Applied Mechanics and Engineering; 2022, 27, 4; 52--65
1734-4492
2353-9003
Pojawia się w:
International Journal of Applied Mechanics and Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of a modified ant colony algorithm for order scheduling in food processing plants
Autorzy:
Korobiichuk, Igor
Hrybkov, Serhii
Seidykh, Olga
Ovcharuk, Volodymyr
Ovcharuk, Andrii
Powiązania:
https://bibliotekanauki.pl/articles/2204558.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
order fulfillment planning
modified ant colony algorithm
efficiency of the algorithms
optimization
food industry
Opis:
This developed modified ant colony algorithm includes an additional improvement with local optimization methods, which reduces the time required to find a solution to the problem of optimization of combinatorial order sequence planning in a food enterprise. The planning problem requires consideration of a number of partial criteria, constraints, and an evaluation function to determine the effectiveness of the established version of the order fulfillment plan. The partial criteria used are: terms of storage of raw materials and finished products, possibilities of occurrence and processing of substandard products, terms of manufacturing orders, peculiarities of fulfillment of each individual order, peculiarities of use of technological equipment, expenses for storage and transportation of manufactured products to the end consumer, etc. The solution of such a problem is impossible using traditional methods. The proposed algorithm allows users to build and reconfigure plans, while reducing the time to find the optimum by almost 20% compared to other versions of algorithms.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 1; 53--61
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine learning algorithms for the problem of optimizing the distribution of parcels in time-dependent networks: the case study
Autorzy:
Tarapata, Zbigniew
Kulas, Wojciech
Antkiewicz, Ryszard
Powiązania:
https://bibliotekanauki.pl/articles/2124716.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
parcel distribution
optimization
machine learning algorithms
time-dependent networks
dystrybucja przesyłek
optymalizacja
algorytmy uczenia maszynowego
sieci zależne czasowo
Opis:
In the paper we present machine learning algorithms for the problem of optimizing the distribution of parcels in stochastic time-dependent networks, which have been built as a part of some Distribution Optimization System. The problem solved was a modified VRPTW (Vehicle Routing Problem with Time Windows) with many warehouses, a heterogeneous fleet, travel times depending on the time of departure (stochastic time-dependent network) and an extensive cost function as an optimization criterion. To solve the problem a modified simulated annealing (SATM) algorithm has been proposed. The paper presents the results of the algorithm learning process: the calibration of input parameters and the study of the impact of parameters on the quality of the solution (calculation time, transport cost function value) depending on the type of input data. The idea is to divide the input data into classes according to a proposed classification rule and to propose several strategies for selecting the optimal set of calibration parameters. These strategies consist in solving some multi-criteria optimization tasks in which four criterion functions are used: the length of the designated routes, the computation time, the number of epochs used in the algorithm, the number of designated routes. The subproblem was building a network model of travel times that is used in constructed SATM algorithm to determine the travel time between recipients, depending on the time of departure from the start location. An attempt has been made to verify the research hypothesis that the time between two points can be estimated with sufficient accuracy depending on their geographical location and the time of departure (without reference to the micro-scale, i.e. the detailed structure of the road network). The research was conducted on two types of data for Warsaw: from transport companies and one of the Internet traffic data providers. Learning the network model of travel times has produced very promising results, which will be described in the paper.
Źródło:
Archives of Transport; 2022, 61, 1; 133--147
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of the process of restoring the continuity of the WDS based on the matrix and genetic algorithm approach
Autorzy:
Antonowicz, Ariel
Urbaniak, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/2173692.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
WNTR
Water Network Tool for Resilience
aggregation of failures
water distribution system
EPANET Solver
Graph Searching Algorithms
genetic algorithm
optimization
post-disaster events
agregacja awarii
system dystrybucji wody
EPANET
algorytm wyszukiwania grafów
algorytm genetyczny
optymalizacja
wydarzenia po katastrofie
Opis:
The article discusses an example of the use of graph search algorithms with trace of water analysis and aggregation of failures in the occurrence of a large number of failures in the Water Supply System (WSS). In the event of a catastrophic situation, based on the Water Distribution System (WDS) network model, information about detected failures, the condition and location of valves, the number of repair teams, criticality analysis, the coefficient of prioritization of individual network elements, and selected objective function, the algorithm proposes the order of repairing the failures should be analyzed. The approach proposed by the authors of the article assumes the selection of the following objective function: minimizing the time of lack of access to drinking water (with or without prioritization) and minimizing failure repair time (with or without failure aggregation). The algorithm was tested on three different water networks (small, medium, and large numbers of nodes) and three different scenarios (different numbers of failures and valves in the water network) for each selected water network. The results were compared to a valve designation approach for closure using an adjacency matrix and a Strategic Valve Management Model (SVMM).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 4; art. no. e141594
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Algorytm inspirowany polem walki - połączenie algorytmów numerycznych z ideą roju
Autorzy:
Baumgart, Jan
Sangho, Belco
Powiązania:
https://bibliotekanauki.pl/articles/41206049.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
algorytm optymalizacyjny
inspiracja polem walki
rozwiązanie
optymalizacja
rzeczywiste problemy optymalizacji
optymalizacja funkcji
algorytm numeryczny
optimization algorithms
battlefield inspired inspiration
solution
optimization
real optimization problems
function optimization
numerical algorithm
Opis:
Artykuł przedstawia przygotowany algorytm na bazie połączenia idei znanych metod numerycznych z metodami opartymi na idei roju. Algorytm został przygotowany z inspiracji polem walki podczas którego w równych odstępach żołnierze przeczesują siły wroga z różnymi prędkościami zależnie od posiadanego orężu a następnie ograniczają zakres pola bitwy. Zaproponowane rozwiązanie wywodzi się właśnie ze zbliżonych założeń. Głównym założeniem pracy było przedstawienie potencjalnego zysku z połączenia metod optymalizacji oraz porównanie metody mieszanej z metodami bazującymi na idei roju pod względem prędkości działania oraz skuteczności odnajdowania optimum globalnego.Algorytm został porównany z dwoma algorytmami metaheurystycznymi pod kątem dokładności odnalezionych rozwiązań oraz prędkości. Zgodnie z wynikami eksperymentów posiada wydajność podobną w porównaniu z innymi algorytmami oraz daje zadowalające efekty w wykorzystaniu.
he article presents prepared algorithm based on the combination of the ideas of known numericalmethods with methods based on the idea of a swarm. The algorithm was prepared inspired by the battlefield,during which, at equal intervals, soldiers scour enemy forces at different speeds depending on the weapon theyhave, and then limit the scope of the battlefield. The proposed solution is based on similar assumptions. Themain assumption of the work was to present the potential profit from the combination of optimization methodsand to compare the mixed method with methods based on the idea of a swarm in terms of operating speed andthe effectiveness of finding the global optimum. The algorithm was compared with two metaheuristic algorithmsin terms of the accuracy of the solutions found and speed. According to the results of the experiments, it hasa similar performance compared to other algorithms and gives satisfactory results in use.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2021, 2; 26-31
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Allocation of real power generation based on computing over all generation cost: an approach of Salp Swarm Algorithm
Autorzy:
Devarapalli, Ramesh
Sinha, Nikhil Kumar
Rao, Bathina Venkateswara
Knypiński, Łukasz
Lakshmi, Naraharisetti Jaya Naga
García Márquez, Fausto Pedro
Powiązania:
https://bibliotekanauki.pl/articles/1841291.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
economic load dispatch
heuristic algorithms
optimization
Particle Swarm
Algorithm
Salp Swarm Algorithm
ekonomiczna wysyłka ładunku
algorytmy heurystyczne
optymalizacja
rój cząstek
algorytm
Opis:
Economic Load Dispatch (ELD) is utilized in finding the optimal combination of the real power generation that minimizes total generation cost, yet satisfying all equality and inequality constraints. It plays a significant role in planning and operating power systems with several generating stations. For simplicity, the cost function of each generating unit has been approximated by a single quadratic function. ELD is a subproblem of unit commitment and a nonlinear optimization problem. Many soft computing optimization methods have been developed in the recent past to solve ELD problems. In this paper, the most recently developed population-based optimization called the Salp Swarm Algorithm (SSA) has been utilized to solve the ELD problem. The results for the ELD problem have been verified by applying it to a standard 6-generator system with and without due consideration of transmission losses. The finally obtained results using the SSA are compared to that with the Particle Swarm Optimization (PSO) algorithm. It has been observed that the obtained results using the SSA are quite encouraging.
Źródło:
Archives of Electrical Engineering; 2021, 70, 2; 337-349
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial Neural Network Optimized by Modified Particle Swarm Optimization for Predicting Peak Particle Velocity Induced by Blasting Operations in Open Pit Mines
Autorzy:
Bui, Xuan‑Nam
Nguyen, Hoang
Nguyen, Truc Anh
Powiązania:
https://bibliotekanauki.pl/articles/2020892.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
blast-induced ground vibration
peak particle velocity
open pit mine
artificial neural network
modified particle swarm optimization
metaheuristic algorithms
wibracje gruntu wywołane podmuchami
drgania górotworu
górnictwo odkrywkowe
sztuczne sieci neuronowe
Opis:
Blasting is an indispensable part of the open pit mining operations. It plays a vital role in preparing the rock mass for subsequent operations, such as loading/unloading, transporting, crushing, and dumping. However, adverse effects, especially blast-induced ground vibrations, are considered one of the most dangerous problems. In this study, artificial intelligence was supposed to predict the intensity of blast-induced ground vibration, which is represented by the peak particle velocity (PPV). Accordingly, an artificial neural network was designed to predict PPV at the Coc Sau open pit coal mine with 137 blasting events were collected. Aiming to optimize the ANN model, the modified version of the particle swarm optimization (MPSO) algorithm was applied to optimize the ANN model for predicting PPV, called the MPSO-ANN model. For the comparison purposes, two forms of empirical equations, namely United States Bureau of Mining (USBM) and U Langefors - Kihlstrom, were also developed to predict PPV and compared with the proposed MPSO-ANN model. The results showed that the proposed MPSO-ANN model provided a better performance with a mean absolute error (MAE) of 1.217, root-mean-squared error (RMSE) of 1.456, and coefficient of determination (R2) of 0.956. Meanwhile, the empirical models only provided poorer performances with an MAE of 1.830 and 2.012, RMSE of 2.268 and 2.464, and R2 of 0.874 and 0.852 for the USBM and U Langefors – Kihlstrom empirical models, respectively.
Źródło:
Inżynieria Mineralna; 2021, 2; 79--90
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Constrained optimization of line-start PM motor based on the gray wolf optimizer
Autorzy:
Knypińskia, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/1841785.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
heuristic algorithms
gray wolf algorithm
constrained optimization
external penalty function
line-start PM synchronous motor
Opis:
This paper presents the algorithm and computer software for constrained optimization based on the gray wolf algorithm. The gray wolf algorithm was combined with the external penalty function approach. The optimization procedure was developed using Borland Delphi 7.0. The developed procedure was then applied to design of a line-start PM synchronous motor. The motor was described by three design variables which determine the rotor structure. The multiplicative compromise function consisted of three maintenance parameters of designed motor and one non-linear constraint function was proposed. Next, the result obtained for the developed procedure (together with the gray wolf algorithm) was compared with results obtained using: (a) the particle swarm optimization algorithm, (b) the bat algorithm and (c) the genetic algorithm. The developed optimization algorithm is characterized by good convergence, robustness and reliability. Selected results of the computer simulation are presented and discussed.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 1; 1-10
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Direct least squares and derivative-free optimisation techniques for determining mine-induced horizontal ground displacement
Autorzy:
Rusek, Janusz
Tajduś, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/2090675.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
horizontal ground displacement
mining
direct least squares
derivative-free optimisation
genetic algorithms
differential evolution
particle swarm optimization
przemieszczenie poziome gruntu
górnictwo
optymalizacja bez pochodnych
optymalizacja roju cząstek
algorytmy genetyczne
ewolucja różnicowa
bezpośrednie najmniejsze kwadraty
Opis:
The paper presents the results of analyses concerning a new approach to approximating trajectory of mining-induced horizontal displacements. Analyses aimed at finding the most effective method of fitting data to the trajectory of mining-induced horizontal displacements. Two variants were made. In the first, the direct least square fitting (DLSF) method was applied based on the minimization of the objective function defined in the form of an algebraic distance. In the second, the effectiveness of differential-free optimization methods (DFO) was verified. As part of this study, the following methods were tested: genetic algorithms (GA), differential evolution (DE) and particle swarm optimization (PSO). The data for the analysis were measurements of on the ground surface caused by the mining progressive work at face no. 698 of the German Prospel-Haniel mine. The results obtained were compared in terms of the fitting quality, the stability of the results and the time needed to carry out the calculations. Finally, it was found that the direct least square fitting (DLSF) approach is the most effective for the analyzed registration data base. In the authors’ opinion, this is dictated by the angular range in which the measurements within a given measuring point oscillated.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; e135840, 1--12
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Direct least squares and derivative-free optimisation techniques for determining mine-induced horizontal ground displacement
Autorzy:
Rusek, Janusz
Tajduś, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/2173560.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
horizontal ground displacement
mining
direct least squares
derivative-free optimisation
genetic algorithms
differential evolution
particle swarm optimization
przemieszczenie poziome gruntu
górnictwo
optymalizacja bez pochodnych
optymalizacja roju cząstek
algorytmy genetyczne
ewolucja różnicowa
bezpośrednie najmniejsze kwadraty
Opis:
The paper presents the results of analyses concerning a new approach to approximating trajectory of mining-induced horizontal displacements. Analyses aimed at finding the most effective method of fitting data to the trajectory of mining-induced horizontal displacements. Two variants were made. In the first, the direct least square fitting (DLSF) method was applied based on the minimization of the objective function defined in the form of an algebraic distance. In the second, the effectiveness of differential-free optimization methods (DFO) was verified. As part of this study, the following methods were tested: genetic algorithms (GA), differential evolution (DE) and particle swarm optimization (PSO). The data for the analysis were measurements of on the ground surface caused by the mining progressive work at face no. 698 of the German Prospel-Haniel mine. The results obtained were compared in terms of the fitting quality, the stability of the results and the time needed to carry out the calculations. Finally, it was found that the direct least square fitting (DLSF) approach is the most effective for the analyzed registration data base. In the authors’ opinion, this is dictated by the angular range in which the measurements within a given measuring point oscillated.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; art. no. e135840
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dissemination of algorithms for decision-making aiding in the design of furniture and other products made of lignocellulosic materials in the scientific literature
Autorzy:
Jasińska, Anna
Sydor, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/2146682.pdf
Data publikacji:
2021
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
furniture
lignocellulosic materials
optimization algorithms
meble
materiały lignocelulozowe
algorytmy optymalizacji
Opis:
Dissemination of algorithms for decision-making aiding in the design of furniture and other products made of lignocellulosic materials in the scientific literature. The issue of the proper selection of dimensions of the designed products can be supported with the use of mathematical algorithms built into CAD systems. There are many such algorithms, they have their specificity and areas of application. The article lists a dozen or so of the most popular algorithms of this type, and then checks their prevalence in the scientific literature on furniture design. The result is a point the method (group of methods) that best takes into account the specific features of lignocellulosic materials. The main conclusion is that the most popular algorithms are: the ε-constraint method, genetic algorithms and artificial immune systems. The most popular is the ε-constraint method.
Upowszechnienie w literaturze naukowej algorytmów wspomagających podejmowanie decyzji w projektowaniu mebli i innych wyrobów z materiałów lignocelulozowych. Zagadnienie właściwego doboru wymiarów projektowanych wyrobów może być wspomagane za pomocą algorytmów matematycznych wbudowanych w systemy CAD. Takich algorytmów jest wiele, mają one swoją specyfikę i obszary zastosowań. W artykule wymieniono kilkanaście najpopularniejszych algorytmów tego typu, a następnie sprawdzono ich rozpowszechnienie w literaturze naukowej dotyczącej projektowania mebli. Wynikiem jest metoda punktowa (grupa metod), która najlepiej uwzględnia specyficzne cechy materiałów lignocelulozowych. Główny wniosek jest taki, że najpopularniejsze algorytmy to: metoda ε-ograniczenia, algorytmy genetyczne i sztuczne układy odpornościowe. Najpopularniejsza jest metoda z ograniczeniem.
Źródło:
Annals of Warsaw University of Life Sciences - SGGW. Forestry and Wood Technology; 2021, 113; 60--64
1898-5912
Pojawia się w:
Annals of Warsaw University of Life Sciences - SGGW. Forestry and Wood Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 127

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