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Wyświetlanie 1-15 z 101
Tytuł:
Support vector regression tree model for the embankment breaching analysis based on the Chamoli tragedy in Uttarakhand
Autorzy:
Sitender
Verma, Deepak Kumar
Setia, Baldev
Powiązania:
https://bibliotekanauki.pl/articles/36073899.pdf
Data publikacji:
2024
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
embankment breaching
multi-objective data
catastrophic collapses
rock-ice avalanche
Chamoli tragedy
Opis:
This study used the analysis to provide considerable support of historical distortion in the Himalayan Chamoli tragedy of 2021. According to multi-objective data and survey results, a precursor event occurred in 2016, and a linear fracture grew at joint planes, suggesting that the 2021 rock ice avalanche will fail retrogressively. To analyze breaching, this study considers seven distinct criteria such as slope, water pressure, and faulty drainage, hydrostatic stress, agricultural operations, cloudbursts, and road building. Based on these characteristics, the support vector regression (SVR) model is utilized to analyze the sensitivity of the link between these parameters. The application of support vector regression analysis on the Chamoli instance confirmed our conclusion that embankment breaching causes glacier retreat and other consequences in increasing sensitivity to the characteristics of fractured rock masses in tectonically active mountain belts. Recent advances in environmental monitoring and geological monitoring systems can be used with the proposed SVR model to provide further information on the location and time of the impending catastrophic collapses in high hill regions.
Źródło:
Scientific Review Engineering and Environmental Sciences; 2024, 33, 1; 95-111
1732-9353
Pojawia się w:
Scientific Review Engineering and Environmental Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybridization of machine learning and NSGA-II for multi-objective optimization of surface roughness and cutting force in AISI 4340 alloy steel turning
Autorzy:
Nguyen, Anh-Tu
Nguyen, Van-Hai
Le, Tien-Thinh
Nguyen, Nhu-Tung
Powiązania:
https://bibliotekanauki.pl/articles/2200263.pdf
Data publikacji:
2023
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
multi-objective optimisation
machine learning
AISI 4340
NSGA-II
ANN
Opis:
This work focuses on optimizing process parameters in turning AISI 4340 alloy steel. A hybridization of Machine Learning (ML) algorithms and a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is applied to find the Pareto solution. The objective functions are a simultaneous minimum of average surface roughness (Ra) and cutting force under the cutting parameter constraints of cutting speed, feed rate, depth of cut, and tool nose radius in a range of 50–375 m/min, 0.02–0.25 mm/rev, 0.1–1.5 mm, and 0.4–0.8 mm, respectively. The present study uses five ML models – namely SVR, CAT, RFR, GBR, and ANN – to predict Ra and cutting force. Results indicate that ANN offers the best predictive performance in respect of all accuracy metrics: root-mean-squared-error (RMSE), mean-absolute-error (MAE), and coefficient of determination (R2). In addition, a hybridization of NSGA-II and ANN is implemented to find the optimal solutions for machining parameters, which lie on the Pareto front. The results of this multi-objective optimization indicate that Ra lies in a range between 1.032 and 1.048 μm, and cutting force was found to range between 7.981 and 8.277 kgf for the five selected Pareto solutions. In the set of non-dominated keys, none of the individual solutions is superior to any of the others, so it is the manufacturer's decision which dataset to select. Results summarize the value range in the Pareto solutions generated by NSGA-II: cutting speeds between 72.92 and 75.11 m/min, a feed rate of 0.02 mm/rev, a depth of cut between 0.62 and 0.79 mm, and a tool nose radius of 0.4 mm, are recommended. Following that, experimental validations were finally conducted to verify the optimization procedure.
Źródło:
Journal of Machine Engineering; 2023, 23, 1; 133--153
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:
Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:
https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:
One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
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:
A Survey on multi-objective based parameter optimization for deep learning
Autorzy:
Chakraborty, Mrittika
Pal, Wreetbhas
Bandyopadhyay, Sanghamitra
Maulik, Ujjwal
Powiązania:
https://bibliotekanauki.pl/articles/27312917.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
deep learning
multi-objective optimization
parameter optimization
neural networks
Opis:
Deep learning models form one of the most powerful machine learning models for the extraction of important features. Most of the designs of deep neural models, i.e., the initialization of parameters, are still manually tuned. Hence, obtaining a model with high performance is exceedingly time-consuming and occasionally impossible. Optimizing the parameters of the deep networks, therefore, requires improved optimization algorithms with high convergence rates. The single objective-based optimization methods generally used are mostly time-consuming and do not guarantee optimum performance in all cases. Mathematical optimization problems containing multiple objective functions that must be optimized simultaneously fall under the category of multi-objective optimization sometimes referred to as Pareto optimization. Multi-objective optimization problems form one of the alternatives yet useful options for parameter optimization. However, this domain is a bit less explored. In this survey, we focus on exploring the effectiveness of multi-objective optimization strategies for parameter optimization in conjunction with deep neural networks. The case studies used in this study focus on how the two methods are combined to provide valuable insights into the generation of predictions and analysis in multiple applications.
Źródło:
Computer Science; 2023, 24 (3); 327--359
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Design optimization of compliant mechanisms for vibration assisted machining applications using a hybrid Six Sigma, RSM-FEM, and NSGA-II approach
Autorzy:
Pham, Huy-Tuan
Nguyen, Van-Khien
Dang, Quang-Khoa
Duong, Thi Van Anh
Nguyen, Duc-Thong
Phan, Thanh-Vu
Powiązania:
https://bibliotekanauki.pl/articles/24084644.pdf
Data publikacji:
2023
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
compliant mechanism
multi-objective optimisation
Six Sigma
NSGA-II
Opis:
Vibration-assisted machining, a hybrid processing method, has been gaining considerable interest recently due to its advantages, such as increasing material removal rate, enhancing surface quality, reducing cutting forces and tool wear, improving tool life, or minimizing burr formation. Special equipment must be designed to integrate the additional vibration energy into the traditional system to exploit those spectacular characteristics. This paper proposes the design of a new 2-DOF high-precision compliant positioning mechanism using an optimization process combining the response surface method, finite element method, and Six Sigma analysis into a multi-objective genetic algorithm. The TOPSIS method is also used to select the best solution from the Pareto solution set. The optimum design was fabricated to assess its performance in a vibration-assisted milling experiment concerning surface roughness criteria. The results demonstrate significant enhancement in both the manufacturing criteria of surface quality and the design approach criteria since it eliminates modelling errors associated with analytical approaches during the synthesis and analysis of compliant mechanisms.
Źródło:
Journal of Machine Engineering; 2023, 23, 2; 135--158
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm
Autorzy:
Yilmaz, Mehmet
Dede, Tayfun
Grzywiński, Maksym
Powiązania:
https://bibliotekanauki.pl/articles/31342511.pdf
Data publikacji:
2023
Wydawca:
Politechnika Częstochowska
Tematy:
multi-objective optimization
grey wolf optimization algorithm
time-cost-risk
optymalizacja wielocelowa
algorytm optymalizacji szarego wilka
czas-koszt-ryzyko
Opis:
Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.
Źródło:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2023, 12; 79-86
2299-8535
2544-963X
Pojawia się w:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelling of surface roughness and tool wear when finish milling process of the circular bevel gear
Autorzy:
Pham, Van Dong
Hoang, Xuan Thinh
Powiązania:
https://bibliotekanauki.pl/articles/2200262.pdf
Data publikacji:
2023
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
circular bevel gear
surface roughness model
tool wear model
multi-objective optimisation
Opis:
An experimental process to build the models of surface roughness and tool wear in the finish milling of the Gleason circular bevel gears was carried out in this study. The experiments were conducted according to a Box-Behnken matrix. Three cutting parameters were adjusted in each experiment including cutting speed, feed rate, and depth of cut. From the experimental results, the influences of cutting parameters on the surface roughness and tool wear were analysed in detail. Two models of surface roughness and tool wear were established with high accuracy. The optimal values of the cutting parameters were also determined to simultaneously ensure the minimum values of two output parameters. The further research directions were also suggested at the end of this study.
Źródło:
Journal of Machine Engineering; 2023, 23, 1; 154--169
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization for weld track geometry in wire-arc directed energy deposition of ER308L stainless steel
Autorzy:
Nguyen, Van Canh
Le, Van Thao
Pham, Ngoc-Linh
Nguyen, Anh-Thang
Powiązania:
https://bibliotekanauki.pl/articles/24084674.pdf
Data publikacji:
2023
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
wire-arc directed energy deposition
weld track
ER308L stainless steel
multi-objective optimisation
Opis:
In this research, the weld track geometry in wire-arc DED (directed energy deposition) of ER308L stainless steel was predicted and optimized. The studied geometrical attributes of weld tracks include weld track width (WTW), weld track height (WTH), and contact angle (α). The experiment was designed based on Taguchi method with three variables (current I, voltage U, and weld velocity v) and four levels for each variable. The ANOVA was adopted to evaluate the accuracy of the models and impact levels of variables on the responses. The TOPSIS method was utilized to predict the optimal variables. The results indicated that the predicted models were built with high accuracy levels (R2 = 98.92%, 98.77%, and 98.91% for WTW, WTH, and α, respectively). Among the studied variables, U features the highest effects on WTW and α with 78.56% and 69.90% of contribution, respectively, while v is the variable that has the most impact on WTH with 39.82% of contribution. The optimal variables predicted by TOPSIS were U = 23 V, I = 140 A, and v = 300 mm/min, which allows building components with stable and regular geometry.
Źródło:
Journal of Machine Engineering; 2023, 23, 2; 123--134
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of PCM-fin structure for staggered Li-ion battery packs
Autorzy:
Qiu, Chenghui
Wu, Chongtian
Yuan, Xiaolu
Wu, Linxu
Yang, Jiaming
Shi, Hong
Powiązania:
https://bibliotekanauki.pl/articles/27311457.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
staggered arrangement
phase change material
fin
multi-objective optimization
thermal management
entropy weight
TOPSIS method
technique for order of preference by similarity to ideal solution
układ naprzemienny
materiał o przemianie fazowej
materiał zmieniający fazę
płetwa
optymalizacja wielocelowa
optymalizacja wieloobiektowa
zarządzanie ciepłem
entropia wagi
metoda TOPSIS
technika porządkowania preferencji według podobieństwa do idealnego rozwiązania
Opis:
Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e145677
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective two-stage stochastic optimization model for post-disaster waste management
Autorzy:
Boonmee, Chawis
Legsakul, Komkrit
Arimura, Mikiharu
Powiązania:
https://bibliotekanauki.pl/articles/23966900.pdf
Data publikacji:
2023
Wydawca:
Stowarzyszenie Menedżerów Jakości i Produkcji
Tematy:
po katastrofie
gospodarowanie odpadami
wielozadaniowość
dwustopniowy model stochastyczny
post-disaster
waste management
multi-objective
two-stage stochastic model
Opis:
Post-disaster waste management is one of the most crucial tasks in the recovery phase of the disaster cycle, and it was created to assist affected communities in returning to a stable state following a disaster. To develop an efficient post-disaster waste management strategy, this study presents a multi-objective two-stage stochastic mixed integer linear programming model for post-disaster waste management. The proposed mathematical model was developed based on a mixed strategy of on-site and off-site waste separation in the supply chain. This study aims to minimize not only the total cost and the environmental impact to provide waste flow decisions and choose collection and separation sites, recycling sites, landfill sites, and incineration sites throughout the supply chain under the uncertain situation. To solve a multi-objective problem, a normalized weighted sum method is used to find the solution. A numerical case based on realistic data is presented to validate and verify the proposed model. Based on the numerical example, the results demonstrated that the implementation of the mixed strategy for waste separation with the consideration of uncertain situations can reduce the total cost, balance the environmental impact, and determine the unexpected situation in the post-disaster waste supply chain efficiently.
Źródło:
Production Engineering Archives; 2023, 29, 1; 58--68
2353-5156
2353-7779
Pojawia się w:
Production Engineering Archives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal allocation of reliability improvement target based on multiple correlation failures and risk uncertainty
Autorzy:
Jia, Shuoguo
Yan, Changfeng
Kang, Jianxiong
Xie, Heping
Wei, Yongqiao
Powiązania:
https://bibliotekanauki.pl/articles/24200787.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
multi-objective optimal allocation
reliability improvement
correlation failure
risk uncertainty
probability measure
cooperation game theory
PSO algorithm
Opis:
Optimal allocation of the reliability improvement target is essential for the system optimization design. In order to solve the problems that the optimization model is with loss of generality and the validity of the optimal solution is weakened, an optimal allocation method is proposed by considering multiple correlation failures and risk uncertainty in this paper. Two new concepts are presented, such as independent failure results in basic risk, and correlation failure leads to disturbance risk. A risk assessment machinery of “actual risk = basic risk + disturbance risk” is proposed. The action mechanisms of the three correlation failures are studied based on the cooperation game theory, and the generalized risk models are given under probability measure. Considering the improvement cost, the expectation and the variance of the reduction of system risk, a multi-objective optimal allocation model is developed, which is solved by using the PSO algorithm. Finally, the proposed optimal allocation is implemented at the 2-stage NGW planetary reducer, and the results show that it is more efficient and feasible for engineering practice.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 1; art. no. 8
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
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:
An algorithm for quadratically constrained multi-objective quadratic fractional programming with pentagonal fuzzy numbers
Autorzy:
Goyal, Vandana
Rani, Namrata
Gupta, Deepak
Powiązania:
https://bibliotekanauki.pl/articles/2175831.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
multi-objective quadratic fractional programming model
MOQFPM
pentagonal fuzzy number
PFN
mean method of α-cut
parametric approach
ε-constraint method
Opis:
This study proposes a methodology to obtain an efficient solution for a programming model which is multi-objective quadratic fractional with pentagonal fuzzy numbers as coefficients in all the objective functions and constraints. The proposed approach consists of three stages. In the first stage, defuzzification of the coefficients is carried out using the mean method of α-cut. Then, in the second stage, a crisp multi-objective quadratic fractional programming model (MOQFP) is constructed to obtain a non-fractional model based on an iterative parametric approach. In the final stage, this multi- -objective non-fractional model is transformed to obtain a model with a single objective by applying the ε-constraint method. This final model is then solved to get desired solution. Also, an algorithm and flowchart expressing the methodology are given to present a clear picture of the approach. Finally, a numerical example illustrating the complete approach is given.
Źródło:
Operations Research and Decisions; 2022, 32, 1; 49--71
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of goal programming in the textile apparel industry to resolve production planning problems : a meta-goal programming technique using weights
Autorzy:
Malik, Zahid Amin
Kumar, Rakesh
Pathak, Govind
Roy, Haridas
Powiązania:
https://bibliotekanauki.pl/articles/2175839.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
meta-goal programming
weighted goal programming
multi-objective decision making
asset allocation
textile sector
sensitivity analysis
Opis:
In the present business environment, rapidly developing technology and the competitive world market pose challenges to the available assets of industries. Hence, industries need to allocate and use available assets at the optimum level. Thus, industrialists must create a good decision plan to guide their performance in the production sector. As a result, the present study applies the Meta-Goal Programming technique to attain several objectives simultaneously in the textile production sector. The importance of this study lies in pursuing different objectives simultaneously, which has been almost ignored till now. The production scheduling problem in a textile firm is used to illustrate the practicability and mathematical validity of the suggested approach. Analysis of the results obtained demonstrates that the solution met all three meta-goals with some original goals being met partially. An analysis of the sensitivity of the approach to the weights of the preferences was conducted.
Źródło:
Operations Research and Decisions; 2022, 32, 2; 74--88
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
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