Wyniki wyszukiwania - BazTech

1

Optimal design of the Brushed DC motor implemented for car window lifting system using Taguchi method

Knypiński Łukasz, Devarapalli Ramesh, Roszak Sebastian, Kamiński Marcin

Przegląd Elektrotechniczny

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2025

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R. 101, nr 4

134--137

EN

The paper presents the results of the multi-objective optimization of the brushed permanent magnet motor for a car window lifting system. The issue was executed by the use of orthogonal Taguchi tables. Application of the Taguchi method leads to simplified optimization. This is because, during the optimization process, the analysis tasks were computed for pre-defined numbers of the experiments. The number of experiments depends on a number and an assigned variability of a design variables. The motor was described by three variables, describing its structure of the magnetic circuit. The optimality criteria were formed by different combinations of functional parameters of the device. The selected functional parameters are taken into account in the multi-objective function. The mathematical model of the brushed DC motor includes (a) the electromagnetic field equations with non-linearity of the ferromagnetic material, (b) equations of the external supply circuit, and (c) equations of mechanical motion. The selected results of optimization were presented and discussed.

PL

W artykule przedstawiono wyniki wielokryterialnej optymalizacji magnetoelektrycznego silnika prądu stałego do napędu szyb w samochodach. Zadanie wykonano przy wykorzystaniu metody tablic Taguchi. Wspomniany algorytm pozwala na skrócenie czasu trwania obliczeń, bowiem przetwarzanie danych dotyczących rozkładu pola elektromagnetycznego oraz parametrów funkcjonalnych, uwzględnianych w wielkokryterialnej funkcji celu, wykonywane są dla zadanej liczby eksperymentów. Obiekt został opisany przy wykorzystaniu trzech zmiennych decyzyjnych. W procesie optymalizacji uwzględniono wybrane parametry funkcjonalne urządzenia. Model matematyczny silnika magnetoelektrycznego zawierał równania pola elektromagnetycznego z uwzględnieniem nieliniowości obwodu magnetycznego, zależności matematyczne zewnęt

2

Multi-objective optimal reactive power planning using particle swarm optimization

Yadav Sandeep, Saini Sanju

Przegląd Elektrotechniczny

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2025

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R. 101, nr 4

234--237

EN

The enhanced multi-objective deterministic reactive power planning power system presented in this study takes wind power production and load demand uncertainties into account. Reactive power planning comprises of all the planning steps required to improve electricity networks' stability and voltage profile. This study utilizes a Multi-Objective+Particle Swarm Optimization technique to get the most optimum Renewable Power Production (RPP), while considering the inherent uncertainty related to renewable sources. Attaining goals of preserving the high voltage profile while concurrently decreasing the costs linked to the implementation of VAr results in a mutually advantageous conclusion. The test bus system IEEE 30 is utilised to assess the suggested method's efficacy.

PL

Ulepszony wielocelowy deterministyczny system planowania mocy biernej przedstawiony w tym badaniu uwzględnia niepewność produkcji energii wiatrowej i zapotrzebowania na moc. Planowanie mocy biernej obejmuje wszystkie kroki planowania wymagane do poprawy stabilności sieci elektroenergetycznych i profilu napięcia. W tym badaniu wykorzystano technikę optymalizacji wielocelowej + roju cząstek, aby uzyskać najbardziej optymalną produkcję energii odnawialnej (RPP), biorąc pod uwagę nieodłączną niepewność związaną ze źródłami odnawialnymi. Osiągnięcie celów zachowania profilu wysokiego napięcia przy jednoczesnym zmniejszeniu kosztów związanych z wdrożeniem VAr prowadzi do wzajemnie korzystnego wniosku. System magistrali testowej IEEE 30 jest wykorzystywany do oceny skuteczności sugerowanej metody.

3

Multi‍-Criteria‍ optimisation‍ of‍ power flow‍ in distribution‍ networks‍ (MV)‍ with‍ local‍ energy‍ sources‍ using‍ evolutionary‍ algorithms

Filipiak Sylwester

Przegląd Elektrotechniczny

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2025

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R. 101, nr 7

28--36

EN

This article presents methods for multi ‑criteria optimisation of medium ‑voltage (MV) network operation, taking into ac count current operational challenges faced by MV distribution networks. The methodology proposed in this article enables the use of evolutionary algorithms to coordinate the operation of local power sources within the distribution network. This paper presents analyses related to multi ‑criteria optimization using selected evolutionary algorithms and their proposed modifications. The analy ses consider optimization criteria related to minimizing technical losses in medium ‑voltage electricity distribution networks, voltage deviation minimization, reduction of network equipment overloads, and optimal power flow.

PL

W artykule przedstawiono metody wielokryterialnej optymalizacji pracy sieci średniego napięcia (SN), uwzględniające aktualne wyzwania eksploatacyjne, z jakimi borykają się sieci dystrybucyjne SN. Metodologia zaproponowana w artykule umożliwia wykorzystanie algorytmów ewolucyjnych do koordynacji pracy lokalnych źródeł energii w sieci dystrybucyjnej. W artykule przed stawiono analizy związane z wielokryterialną optymalizacją z wykorzystaniem wybranych algorytmów ewolucyjnych i ich proponow anych modyfikacji. W analizach uwzględniono przyjęto kryteria optymalizacyjne dotyczące minimalizacji strat technicznych w ana lizowanych elektroenergetycznych sieciach dystrybucyjnych SN, minimalizacji odchyleń napięcia, minimalizacji przeciążeń urządzeń sieciowych oraz optymalizacji rozpływów mocy ().

4

MOGA-based optimization and performance comparison of plain and multi-lobe hydrodynamic journal bearings

Ahire N. B., Deshmukh D. D.

International Journal of Applied Mechanics and Engineering

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2025

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Vol. 30, no. 4

1--17

EN

Choosing the best hydrodynamic journal bearing (HJB) involves a complex multi-objective optimization challenge that requires balancing load-carrying capacity (LCC), friction loss, oil film temperature increase, and dynamic stability. This research utilizes the multi-objective genetic algorithm (MOGA) to optimize plain, two-lobe, three-lobe, and four-lobe journal bearings under different operating conditions. The variable parameters of HJBs, including rotational speed, clearance, L/D ratio, and load, were taken into account. The optimization process utilized Pareto-based selection, simulated binary crossover, and Gaussian mutation techniques to determine the optimal bearing choice. The three-lobe bearing proved to be the most suitable choice based on its superior load-carrying capacity, minimal temperature rise, reduced friction loss, and overall stability performance. The findings reveal that the four-lobe bearing excels in LCC, while the plain and two-lobe bearings are advantageous for their simple design and low manufacturing costs. These results offer valuable insights for engineers and designers in choosing the most appropriate bearing type based on specific operational needs and performance trade-offs.

5

Analysis of the Applicability of Heat Treatment of EN AC-46000 Alloy Castings Made with Vacuum-Assisted HPDC Technology

Szymczak Tomasz, Pisarek Bogusław, Januszewicz Bartłomiej, Różycka M.

Archives of Foundry Engineering

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2025

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Vol. 25, iss. 1

59--74

EN

The aim of the study was optimization of the technological parameters of the thermal treatment of EN AC-46000 alloy products made in the vacuum aided HPDC technology in the function of simultaneous maximization of the alloy’s mechanical properties with no deformation of the cast’s surface. The produced casts were subjected to thermal treatment T6 according to the elaborated experiment plan. The samples were examined in respect of selected mechanical properties as well as the presence of deformation on the castings surfaces. Also performed was an analysis of the castings microstructure as well as optimization of the technological parameters of the supersaturation and ageing process by means of statistical methods, i.e. the Box-Wilson optimization method (Stage I) and stepwise multiple regression in the Statgraphics software (Stage II). Also, a simulation was carried out, predicting the mechanical properties for the specific supersaturation and ageing parameters, from which optimized values of the setpoints of both processes were obtained. The study presents the results of validation tests of pressure casts subjected to thermal treatment performed according to the previously determined optimal parameters of supersaturation and ageing. These results confirmed the effectiveness of the conducted precipitation hardening treatment.

6

The optimization model of building construction based on BIM and improved NSGA-III algorithm

Wang Meng

Archives of Civil Engineering

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2025

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Vol. 71, nr 2

5--18

EN

Currently, there are difficulties in dealing with higher construction requirements and standards in subway construction management. Therefore, a multi-objective optimization model was constructed based on building information management technology, and an improved non-dominated sorting genetic algorithm III was introduced to optimize the model solution. And experimental verification was conducted. These experiments confirmed that the average HV of the improved algorithm was 0.67, which was higher than the original algorithm’s 0.65, indicating that it had higher convergence and reliability. The solution results of the non-dominated sorting genetic algorithm II showed that the optimized cost was 185.1899 million yuan. The cost of optimizing the original non-dominated sorting genetic algorithm III was 184.6469 million yuan. The total cost of optimizing the research algorithm was 184.1165 million yuan. In addition, the research algorithm had the shortest construction period, ideal cost, and significantly higher quality and safety levels than the comparison algorithms. And its time consumption was only 20 seconds, significantly lower than the comparison algorithms. And its cost was between 183 million to 187.5 million yuan, with higher stability and relatively concentrated distribution of solutions. Overall, the subway construction optimization model based on building information management and non-dominated sorting genetic algorithm III has high effectiveness and can be effectively applied in practical construction management.

7

Optimal allocation of urban land space based on NSGA2

Guo Yi, Bai Chaoqin, Zhao Peiwen

Archives of Civil Engineering

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2025

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Vol. 71, nr 1

157--172

EN

Urban land spatial optimization is one of the important issues in urban planning and land resource management. As the speed advancement of urbanization and the continuous increase of population, the rational use of land resources has become the key to sustainable urban development. Based on this, the study adopts the optimization goals of maximizing gross domestic product (GDP), reducing aerosol optical thickness and non-point source pollution (NPSP) load, and reducing land use change costs and incongruity. Three constraints are set simultaneously, including minimum construction land, water body, and cultivated land area. In addition, a fast non dominated sorting genetic algorithm (NSGA2) with elite strategy is used to address it. The outcomes denoted that the iterative distance of the proposed algorithm on the Bin and Cohen functions was only 0.048%, which was 0.522% lower than that of the NSGA2. Meanwhile, the reverse iteration distance value of this algorithm was only 4.14%, which was 22.76% lower than the adaptive weighted genetic algorithm. In addition, the algorithm’s Spacing value was only 4.28%, and the hypervolume index value was as high as 78.66%. This indicated that the research method had a good optimization effect on the optimal allocation (OA) of land space in urban agglomerations, providing scientific decision-making support for sustainable urban development.

8

Multi-objective optimization of construction project management based on an improved genetic algorithm

Dai Xiaoyan, Xia Wanwan, Xu Yingwen

Archives of Civil Engineering

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2025

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Vol. 71, nr 3

311--323

EN

In construction project management, it is crucial to consider multiple objectives, such as duration and cost, to develop an optimal plan. This paper established a multi-objective optimization model, taking into account the construction period, cost, safety, and quality of projects. A genetic algorithm (GA) was selected as the solution method, and the non-dominated sorting genetic algorithm-II (NSGA-II) was optimized by cat mapping, adaptive crossover, and mutation operators to obtain an improved algorithm for the model solution. Experiments were conducted to evaluate the performance of the designed algorithm. It was found that the improved NSGA-II exhibited superior convergence and diversity when applied to the test functions ZDT1-ZDT3. The mean construction period obtained from the model solution was 124 days, with a cost of 1,204,782 euros. The quality and safety levels achieved were 0.93 and 0.95, respectively, which were significantly better than those obtained by the NSGA-II. These findings demonstrate the reliability of the improved NSGA-II developed in this paper, suggesting its practical applicability.

9

Analysis of building energy efficiency optimization design effectiveness based on multi-objective optimization algorithm

Guo Wei, Dong Yaqiong

Archives of Civil Engineering

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2025

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Vol. 71, nr 3

33--48

EN

With the increasing attention of society to sustainable development and environmental friendly design, building energy saving design has become a research hotspot. In this paper, a method combining multi-objective optimization algorithm and neural network backpropagation strategy is proposed to solve the problem that traditional design methods are difficult to balance multi-objective. By dividing the architectural design problem into multiple sub-problems, each sub-problem corresponds to a design objective, and applying multi-objective optimization technology, the global optimization is realized. The experimental results show that the error of energy consumption prediction model is almost 0, while the error of daylighting prediction model is between 0 and 5, and the average error is about 3. The correlation coefficients of all models exceeded 0.9845, highlighting the excellent performance of neural networks in forecasting accuracy. The BP neural network showed good convergence in 2800 to 3000 iterations, further demonstrating the high efficiency of the method in energy consumption and daylighting prediction. The research not only provides a scientific and feasible strategy for building energy efficiency optimization design, but also enhances its scientific value and practicability through the display of quantitative results.

10

Use of GIS for preventive mammography screening in relation to the change in age bracket by the national health fund

Miłek Marzenna

GIS Odyssey Journal

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2024

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Vol. 4, no. 1

117--130

EN

This paper discusses and demonstrates the use of GIS for the implementation of imaging-based preventive mammography screening due to the change in the age limit of women eligible for free mammography screening by the National Health Fund. What follows is a presentation of how GIS, Business Intelligence systems and external databases storing key patient data were used to develop a new roadmap for the implementation of mammography screening in 2024, taking into account the change related to the decision of the Ministry of Health. The changes had to be implemented in a short period of time and it was necessary to decide where preventive screenings would be performed by stationary methods and where by mobile mammobus. Another challenge was the way in which the ongoing preventive screening campaign was communicated. The effectiveness of the campaign was influenced by a multi-criteria analysis of influencing factors.

11

Reference Tracking with Responsive Minimum-Separation Threat Areas Avoidance Method using PSO Based MPC Control

Pawłowski Piotr

Elektronika : konstrukcje, technologie, zastosowania

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2024

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Vol. 65, Nr 8

44--48

EN

In this paper, we propose a solution for motion control of the object (agent) within a certain region of interest considering distance to actual reference trajectory and the threat posed by occurring hazardous regions of denial. In this application, a PSO (Particle Swarm Optimization) based MPC (Model Predictive Controller) will be designed, with the aim to achieve flexibility and responsiveness to changing environment conditions (such as appearing threats), that will allow for real short-time path adjustments. Presented approach allows for defining required effective separation between the agent and encountered and identified threats, preserving sensitivity for reference tracking errors.

PL

W poniższym artykule, przedstawiamy propozycję rozwiązania umożliwiającego sterowanie ruchem obiektu (agenta) w zadanym obszarze zainteresowania, uwzględniając napotkane obszary zagrożenia oraz zmiany odległości od zadanej trajektorii ruchu. W tym celu zastosowany został kontroler predykcyjny MPC (Model Predictive Controller), wyposażony w optymalizator oparty na metodzie optymalizacji za pomocą roju cząstek PSO (Particle Swarm Optimization). Waściwości takiego kontrolera pozwalają na reagowanie na zmianę warunków otoczenia (takich jak pojawiające się zagrożenia), elastycznie i responsywnie dostosowując i korygując w czasie rzeczywistym krótkoterminową trajektorię. Przedstawiona strategia daje możliwość zdefiniowania efektywnej wymaganej separacji pomiędzy agentem a napotkanymi, zidentyfikowanymi zagrożeniami, jednocześnie zachowując podatność na błędy śledzenia trajektorii.

12

Short term road network Macroscopic Fundamental Diagram parameters and traffic state prediction based on LSTM

Lin Xuanhua, Tan Chaojian, Lin Xiaohui

Archives of Transport

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2024

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Vol. 71, iss. 3

107--126

EN

Macroscopic Fundamental Diagram (MFD) is widely used in traffic state evaluation due to its description of the macro level of urban road network. This study focuses on the discrimination and short-term prediction of macro traffic states in urban road networks, using MFD combined with FCM clustering for state partitioning to characterize different macro states of the road network. To predict the MFD state, this paper builds two LSTMs to perform short-term predictions on two important parameters in MFD: road network weighted flow qw and road network weighted density kw. The parameters of the first three statistical intervals and the predicted time period are used as inputs to output the MFD parameters for the predicted time period. To ensure that the two LSTM structures and hyper-parameters settings can achieve the best prediction performance for MFD, the parameter optimization process of both should be included in the same search framework for hyper-parameters search. Therefore, this paper uses GA algorithm combined with multi-objective particle swarm optimization algorithm as the solving algorithm, with the accuracy of solving two MFD parameters and the accuracy of MFD point positioning as the hyper-parameters solving objectives. The study was validated using actual road network data from Hong Kong, and the results showed that the method proposed in this paper has an MRE prediction error of less than 7.8% for the two parameters of MFD, and can predict the future temporal trend of the two parameters, demonstrating the feasibility of MFD related predictions. The model's prediction of the overall shape and change trajectory trend of MFD is consistent with reality, and some test sets in MFD state prediction show high accuracy, the overall accuracy is 81.45%. To verify the effectiveness of the multi-objective search algorithm, typical LSTM models and RNN models were used for comparison. The experiment proved that the model used in this study performed better in error control and state prediction. This study explores and practices a short term prediction method for road network MFD parameters, MFD status, and their changing trends. Provided path reference for urban road network prediction, traffic control status, and MFD related research.

13

Multi-objective optimization of construction management of expressway engineering based on improved particle swarm optimization algorithm

Liu Xu

Archives of Civil Engineering

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2024

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Vol. 70, nr 3

359--372

EN

Engineering management is an extremely important aspect of construction engineering, and a better management approach can greatly enhance the production profits of enterprises. Traditional management optimization schemes cannot adapt to current technological needs due to their inability to effectively consider the impact of each factor. Therefore, a construction management optimization scheme combining improved particle algorithm and multi-objective optimization was proposed. The improved particle algorithm enhances its performance by introducing adaptive weight and multi-objective optimization ideas. These studies confirmed that the predicted direct cost savings for the project were around 1 million yuan. The total construction period of project was optimized to 380 days, saving 34 days. The optimization technology not only reduced construction costs, but also reflected the problems that could be improved during this construction process. This study contributes to achieving multi-objective balance in the construction management process, effectively improving project efficiency, reducing project costs and risks, and providing scientific support for construction decision-making.

14

Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours

Deng Hua, Zhou Kai

Archives of Civil Engineering

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2024

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Vol. 70, nr 4

477--489

EN

Recently, with the continuous consumption of energy, building energy conservation has been popular in the energy field. In response to the high computational cost, slow convergence speed, and low accuracy of existing optimization design methods for building energy efficiency, this study first built a multi-objective optimization model for building energy efficiency on the ground of the annual energy consumption of buildings and the quantity of uncomfortable hours for users. Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. In order to select the optimal decision variable of the algorithm, the decision parameters were analyzed and found that the performance was optimal when the number of samples, aggregation number and base model were set to 25.3 and 20. The improved multi-objective evolutionary optimization algorithm on the ground of decomposition has average supervolume and running time values of 32416.13 and 1774.58 seconds under office buildings, and 7899.13 and 3616.96 seconds under residential buildings, respectively. In addition, the annual user discomfort time of office buildings is 555.28h, which is lower than other comparison algorithms. In summary, the optimal performance of the algorithm when the decision variable is set to 25.3 and 20. The algorithm proposed by the research institute has superior performance and has certain application value in selecting the optimal solution for building energy-saving design.

15

Analysis of bridge structure selection using a hybrid decision-making technique

Jakiel Przemysław, Fabianowski Dariusz

Archives of Civil Engineering

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2024

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Vol. 70, nr 3

579--593

EN

Implementation of sustainability principles in civil engineering has increased the substantive range of bridge engineering. The consideration of additional criteria, in particular ecological and social ones, requires the design process to be supported by appropriate tools. It refers especially to large bridge elements which affect their load-bearing capacity, e.g. girders or decks. The aim of this paper is to develop an original MCDA (Multi-Criteria Decision Analysis) method as a potential tool to support a decision-making process in the selection of material and design alternatives for bridge main girders. Therefore, an advanced hybrid algorithm was created consisting of the following methods: EA FAHP+FDEMATEL+ZUM (Extent Analysis Fuzzy Analytic Hierarchy Process + Fuzzy Decision-Making Trial and Evaluation Laboratory + Zero Unitarization Method), applied at the structure design stage. The pre-dimensioned alternatives selected for analysis were then subjected to an evaluation process based on a complex set of criteria arranged in a hierarchical control structure (HCS). The algorithm has been applied based on the example of a medium span slab-and-girder bridge, assuming 6 alternative concepts of girders, different in material and dimensions. The hybrid method was compared with the EA FAHP method. Analysis results obtained based on judgments from 3 teams of Decision Makers (DM) indicate effectiveness of the proposed algorithm and its practical aspect, which may contribute to improved quality and safety of bridge structures.

PL

Celem artykułu jest opracowanie oryginalnej metody MCDA, jako narzędzia wspierającego proces podejmowania decyzji przy wyborze wariantów materiałowo-konstrukcyjnych mostowych dźwigarów głównych. W związku z tym stworzono zaawansowany algorytm hybrydowy, składający się z metod EA FAHP + FDEMATEL + MUZ (Metoda Unitaryzacji Zerowanej), stosowany na etapie projektowania konstrukcji. Rozpoznanie literatury z przedmiotowego zagadnienia wskazuje na brak publikacji. Wybrane do celów analizy, uprzednio zwymiarowane warianty zostały następnie poddawane procesowi oceny na podstawie złożonego zbioru kryteriów, transponowanych na sterującą strukturę hierarchiczną (HCS). Aplikację algorytmu wykonano na przykładzie mostu płytowo-belkowego o średniej rozpiętości przęsła, przyjmując 6 alternatywnych koncepcji dźwigarów. Uzyskane wyniki analizy, porównane z metodą EA FAHP wskazują na efektywność proponowanego algorytmu oraz jego aspekt praktyczny, mogący się przyczynić do podniesienia jakości i bezpieczeństwa konstrukcji mostowych. Do głównych cech proponowanego modelu należy zaliczyć: strukturę sterującą HCS, umożliwiającą szybkie dostosowanie algorytmu do zmian wymogów technicznych i uwarunkowań rynkowych, możliwość uwzględnienia w procesie projektowania nietypowych rozwiązań, np. dźwigarów kompozytowych, uniwersalność w zastosowaniu dla innych rodzajów konstrukcji budowlanych. Za najbardziej znaczący wkład niniejszych badań uznano uwzględnienie interakcji pomiędzy kryteriami. Charakteryzuje je niezmienność w funkcji czasu, osiągana jako efekt długoterminowy dzięki agregacji ocen.

16

Multi-criteria comparative analysis of GIS class systems

Miłek Marzenna, Stanik Jerzy, Kiedrowicz Maciej, Napiórkowski Jarosław

GIS Odyssey Journal

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2023

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Vol. 3, no. 1

97--122

EN

The article discusses a multi-criteria comparative analysis of GIS class computer systems using the Pareto method . Referring to this problem, to find a GIS system (a compromise solution) that would be acceptable for each decision criterion, to make a Pareto optimal decision, multi-criteria optimization was obligatory. To find the mentioned optimum (the Pareto optimum), it is necessary for the decision maker to make a choice concerning the set of admissible decision solutions. Here, a matrix of criteria constructed by the authors is available, filled in with appropriate weights by field experts. This structure is very useful when evaluating the admissible solutions of the resulting algorithm. The space of acceptable solutions in the considered problem task is a set of systems, limited to their eighteen instances, which meet the criterion of completeness of all data required in the conducted research. The selected criteria are the most widely used and most accepted in the environments that systems of this class use daily.

17

A hybrid evolutionary algorithm of optimized controller placement in sdn environment

Hemagowri J., Tamil Selvan P.

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 4

539--556

EN

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.

18

Resilience-based multi-objective optimization for determining the optimal sequence of bridge retrofit projects

Nezhad Mehdi Dezfuli, Raoufi Reza, Dalvand Ahmad

Roads and Bridges - Drogi i Mosty

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2022

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Vol. 21, no. 4

293--308

EN

This study intends to provide a methodology for determination of the optimal sequence of bridge retrofit projects in the pre-disaster phase. A two-stage optimization model is proposed. In the first stage, single-objective optimization is used, and the weighted average number of reliable independent pathways (WIPW) is adopted as the measure of network resilience (MOR) to be maximized. In the second stage, multi-objective optimization is used, and two objective functions are introduced to be maximized: the measure of strategy implementation sequence (MOS) and the measure of strategy implementation time (MOT). The proposed methodology is illustrated using a hypothetical community road system. The results show that there is an inverse relationship between MOS and MOT. By considering these two new objectives in the process of pre-disaster risk mitigation planning, network owners can determine the trade-off between MOS and MOT and select a proper sequence of bridge retrofit projects based on predictability of the examined disruptive events.

PL

Celem pracy jest przedstawienie metodyki określania optymalnej kolejności planowanych modernizacji obiektów mostowych w fazie poprzedzającej wystąpienie katastrofy budowlanej. Zaproponowano dwustopniowy model optymalizacji. W pierwszym etapie wykorzystuje się optymalizację jednokryterialną, a jako miarę zapewnienia maksymalnej odporności na zakłócenia sieci transportowej (MOR) przyjmuje się średnią ważoną z liczby niezawodnych, niezależnych ścieżek (WIPW) między jej węzłami. W drugim etapie stosowana jest optymalizacja wielokryterialna, przy czym dla osiągnięcia maksymalnej odporności na zakłócenia sieci wprowadza się dwie funkcje celu: miarę kolejności wdrażania strategii (MOS) oraz miarę czasu realizacji strategii (MOT). Proponowaną metodykę zilustrowano na przykładzie hipotetycznej sieci dróg lokalnych. Wyniki przeprowadzonej analizy wykazały, że między parametrami MOS i MOT występuje korelacja ujemna. Uwzględniając te dwie nowe funkcje celu w procesie planowania ograniczenia ryzyka przed katastrofą, zarządcy dróg mogą określić kompromis w relacji pomiędzy wartościami MOS oraz MOT i w ten sposób w oparciu o analizę przewidywalności wystąpienia zdarzeń zaburzających funkcjonowanie sieci transportowej dokonać wyboru optymalnej kolejności modernizacji obiektów mostowych.

19

Zintegrowane podejście do wyboru optymalnej serii zapraw tynkarskich do izolacji

Demir Abdullah

Cement Wapno Beton

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2022

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R. 27, nr 1

32--44

PL

W niniejszym artykule zaproponowano metodę Taguchiego do rozwiązania hierarchicznej analizy problemu decyzyjnego [Analytic Hierarchy Process - AHP] oraz metodę Simple Additive Weighting [SAW] w celu znalezienia optymalnej serii zapraw tynkarskich do izolacji, w oparciu o wiele kryteriów. Najpierw zastosowano metodę Taguchi w celu określenia planu eksperymentu z czynnikami: cementem, wapnem, dolomitem i perlitem na trzech poziomach dozowania, dla każdego z nich z ortogonalnym planem L9. Następnie, zgodnie z projektem, przeprowadzono eksperymenty metodą ultradźwiękową, określono wytrzymałość na ściskanie, przyczepność, nasiąkliwość kapilarną i przewodność cieplną. Wagi ważności kryteriów uzyskano metodą AHP, a punktację poszczególnych serii obliczono metodą SAW. Na podstawie wyników uzyskano optymalne poziomy czynników i otrzymano optymalne składy.

EN

In this study, an integrated approach by Taguchi, Analytic Hierarchy Process [AHP] and Simple Additive Weighting [SAW] method was proposed to find out the optimal insulation plaster mortar series, based on multiple criteria. Firstly, Taguchi method was applied to define the experimental design plan, with the factors of cement, lime, dolomite and perlite in three levels for each with L9 orthogonal design. Then, ultrasonic pulse velocity, compressive strength, bond strength, capillarity water absorption and thermal conductivity experiments, were made according to the design. The importance weights of criteria were obtained by AHP and the scores of the series were calculated by SAW method. The factors’ optimum levels were obtained based on the scores and the optimal series was proposed.

20

Multicriteria compromise optimization of feed grain grinding process

Kupchuk Ihor, Yaropud Vitalii, Hraniak Valerii, Poberezhets Julia, Tokarchuk Oleksiy, Hontar Volodymyr, Didyk Andrii

Przegląd Elektrotechniczny

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2021

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R. 97, nr 11

179--183

EN

Optimization of the feed grinding process by a vibrating rotary crusher was carried out and shown in the article: a multifactor experiment was carried out, a statistical analysis of the results was carried out using the software "Statistica 10.0", mathematical models were obtained in the form of multiple regression of the second order and their adequacy was checked by the Fisher criterion. Rational operating parameters were obtained by Cramer's method using the “Mathcad 15.0” software.

PL

Przeprowadzono i przedstawiono w artykule optymalizację procesu rozdrabniania ziarna przez wibracyjną kruszarkę obrotową: przeprowadzono eksperyment wieloczynnikowy, przeprowadzono analizę statystyczną wyników za pomocą programu „Statistica 10.0”, modele matematyczne uzyskano w forma regresji wielokrotnej drugiego rzędu i ich adekwatność sprawdzono za pomocą kryterium Fishera. Racjonalne parametry pracy uzyskano metodą Cramera przy użyciu programu „Mathcad 15.0”.