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1

Design of aspheric spectacle lenses using non-dominated sorting genetic algorithm

Xiang Huazhong, Ding Qihui, Li Nianning, Zhang Xin, Wang Peng, Li Hongtao, Zheng Zexi, Zhang Dawei

Optica Applicata

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2023

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Vol. 53, nr 4

643--654

EN

Significance: An effective algorithm for optimization of lens parameter can greatly eliminate the aberration and reduce the thickness, making the wearer more comfortable. Aim: We proposed a non-dominated sorting genetic algorithm (NSGA-II) for generating sets of base curves and aspheric coefficients to minimize the residual astigmatism and aberration of the lenses, while satisfying the constraints on the lens thickness and power. Approach: By simulating natural selection using the NSGA-II algorithm, the design parameters considered the inventory of the semi-finished blank. A comparison of aspheric and spherical spectacle lenses with –8 diopters was designed, simulated, processed, and measured. Results: The measured spherical and cylindrical power distributions were consistent with the simulated results with corrected oblique astigmatism and distortion. Conclusions: The aspheric spectacle lenses had the required aesthetic shape and weight reduction compared to a spherical lenses of the same power. It is verified that this paper puts forward an effective NSGA-II algorithm for the optimization of lens parameters.

2

Multi-objective optimization for weld track geometry in wire-arc directed energy deposition of ER308L stainless steel

Nguyen Van Canh, Le Van Thao, Pham Ngoc-Linh, Nguyen Anh-Thang

Journal of Machine Engineering

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2023

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Vol. 23, No. 2

123--134

EN

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.

3

Modelling of surface roughness and tool wear when finish milling process of the circular bevel gear

Pham Van Dong, Hoang Xuan Thinh

Journal of Machine Engineering

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2023

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Vol. 23, No. 1

154--169

EN

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.

4

Design optimization of compliant mechanisms for vibration assisted machining applications using a hybrid Six Sigma, RSM-FEM, and NSGA-II approach

Pham Huy-Tuan, Nguyen Van-Khien, Dang Quang-Khoa, Duong Thi Van Anh, Nguyen Duc-Thong, Phan Thanh-Vu

Journal of Machine Engineering

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2023

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Vol. 23, No. 2

135--158

EN

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.

5

A hybridization of machine learning and NSGA-II for multi-objective optimization of surface roughness and cutting force in AISI 4340 alloy steel turning

Nguyen Anh-Tu, Nguyen Van-Hai, Le Tien-Thinh, Nguyen Nhu-Tung

Journal of Machine Engineering

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2023

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Vol. 23, No. 1

133--153

EN

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.

6

Multi-objective optimisation of the electric wheelchair ride comfort and road holding based on jourdain’s principle model and genetic algorithm

Belhorma Mohamed, Bouchikhi Aboubakar Seddik

Acta Mechanica et Automatica

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2022

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Vol. 16, no. 1

58--69

EN

The paper addresses the multi-body modelling of an electric wheelchair using Jourdain’s principle. First, a description of the adopted approach was presented. Next, the mathematical equations were developed to obtain the dynamic behaviour of the concerned system. The numerical computation was performed with MATLAB (matrix laboratory: a high performance language of technical computing) and validated by MBD (Multi-Body Dynamics) for Ansys, a professional multi-body dynamics simulation software powered by RecurDyn. Afterwards, the model was treated as an objective function included in genetic algorithm. The goal was to improve the ride quality and the road holding as well as the suspension workspace. The multi-objective optimisation aimed to reduce the Root-Mean-Square (RMS) of the seat’s vertical acceleration, the wheels load and the workspace modulus by varying the bodies’ masses, the spring-damper coefficients and the characteristics of the tires. Acceptable solutions were captured on the Pareto fronts, in contrast to the relatively considerable processing time involved in the use of a random road profile generated by the power spectral density (PSD). During the process, the compatibility and the efficiency of Jourdain’s equations were inspected.

7

The Effect of Different Decision-Making Methods on Multi-Objective Optimisation of Predictive Torque Control Strategy

Gurel Aycan, Zerdali Emrah

Power Electronics and Drives

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2021

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Vol. 6 (41)

289--300

EN

Today, a clear trend in electrification process has emerged in all areas to cope with carbon emissions. For this purpose, the widespread use of electric cars and wind energy conversion systems has increased the attention and importance of electric machines. To overcome limitations in mature control techniques, model predictive control (MPC) strategies have been proposed. Of these strategies, predictive torque control (PTC) has been well accepted in the control of electric machines. However, it suffers from the selection of weighting factors in the cost function. In this paper, the weighting factor associated with the flux error term is optimised by the non-dominated sorting genetic algorithm (NSGA-II) algorithm through torque and flux errors. The NSGA-II algorithm generates a set of optimal solutions called Pareto front solutions, and a possible solution must be selected from among the Pareto front solutions for use in the PTC strategy. Unlike the current literature, three decision-making methods are applied to the Pareto front solutions and the weighting factors selected by each method are tested under different operating conditions in terms of torque ripples, flux ripples, cur-rent harmonics and average switching frequencies. Finally, a decision-making method is recommended.

8

Optimisation of the topping-up process of lubricating oil in medium-speed marine engines

Młynarczak Andrzej, Krzysztof Rudzki

Polish Maritime Research

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2021

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nr 2

78--84

EN

In this paper, we examine the problem of optimising the process of topping up lubricating oil in medium-speed marine engines. This process is one of the methods that can be applied to improve the properties of lubricating oil. The amount of fresh oil added to lubricating oil system always balances its consumption, but the method used to top up depends on the marine engineer. Small amounts of fresh oil can be added at short intervals, or large ones at long intervals, and the element of randomness often plays a significant role here. It would therefore be valuable to find a method that can help the mechanical engineer to choose the right strategy. We apply a multi-criteria optimisation method for this purpose, and assume that the criterion functions depend on the concentration of solid impurities and the alkalinity, which are among the most important aspects of the quality and properties of lubricating oil. These criterion functions form the basis for multi-objective optimisation carried out with the use of the MATLAB computer program.

9

Carpooling Scheme Selection for Taxi Carpooling Passengers: a Multi-Objective Model and Optimisation Algorithm

Xiao Q., He R.-C.

Archives of Transport

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2017

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Vol. 42, iss. 2

85--92

EN

Carpooling has been long deemed a promising approach to better utilizing existing transportation infrastructure, the carpooling system can alleviate the problems of traffic congestion and environmental pollution effectively in big cities. However, algorithmic and technical barriers inhibit the development of taxi carpooling, and it is still not the preferred mode of commute. In order to improve carpooling efficiency in urban, a taxi carpooling scheme based on multi-objective model and optimisation algorithm is presented. In this paper, urban traffic road network nodes were constructed from the perspective of passenger carpooling. A multi-objective taxi carpooling scheme selection model was built based on an analysis of the main influences of carpooling schemes on passengers. This model aimed to minimise get-on-and-get-off distance, carpooling waiting time and arriving at the destination. Furthermore, a two-phase algorithm was used to solve this model. A rapid searching algorithm for feasible routes was established, and the weight vector was assigned by introducing information entropy to obtain satisfying routes. The algorithm is applied to the urban road, the Simulation experimental result indicates that the optimisation method presented in this study is effective in taxi carpooling passengers.

10

Genetic algorithm as a tool for multi-objective optimization of permanent magnet disc motor

Cvetkovski G., Petkovska L.

Archives of Electrical Engineering

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2016

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Vol. 65, nr 2

285--294

EN

The analysed permanent magnet disc motor (PMDM) is used for direct wheel drive in an electric vehicle. Therefore there are several objectives that could be tackled in the design procedure, such as an increased efficiency, reduced iron weight, reduced copper weight or reduced weight of the permanent magnets (reduced rotor weight). In this paper the optimal design of PMDM using a multi-objective genetic algorithm optimisation procedure is performed. A comparative analysis of the optimal motor solution and its parameters in relation to the prototype is presented.

11

Verified methods for computing Pareto sets: General algorithmic analysis

G.-Tóth B., Kreinovich V.

International Journal of Applied Mathematics and Computer Science

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2009

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Vol. 19, no 3

369-380

EN

In many engineering problems, we face multi-objective optimization, with several objective functions f1, . . . , fn. We want to provide the user with the Pareto set-a set of all possible solutions x which cannot be improved in all categories (i.e., for which fj (x') fj (x) for all j and fj(x') > fj(x) for some j is impossible). The user should be able to select an appropriate trade-off between, say, cost and durability. We extend the general results about (verified) algorithmic computability of maxima locations to show that Pareto sets can also be computed.

12

Optimal design of a disk type magneto-rheologic fluid clutch

Jaindl M., Kostinger A., Magele C., Renhart W.

Przegląd Elektrotechniczny

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2007

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R. 83, nr 6

25-29

EN

This paper deals with the optimal design of a disk type clutch used to apply a continuously adjustable torque. Instead of using friction clutches, the application of an electromagnetic particle clutch is discussed. The magnitude of the torque can be regulated by the application of an appropriate magnetic field which is simulated by FEM. Using an Evolutionary Strategy, a stochastic optimization method, a design yielding a prescribed torque subject to geometric constraints is developed.

PL

Praca omawia optymalną konstrukcję sprzęgła tarczowego przy płynnej regulacji momentu. Przedyskutowano zastosowanie sprzęgła elektromagnetycznego w miejsce sprzęgieł ciernych. Moment może być regulowany przez pole magnetyczne. Wykonano symulacje komputerowe z użyciem MES. Opracowano projekt sprzęgła dającego żądany moment przy ograniczeniach geometrycznych, stosując strategię ewolucyjną – stochastyczną metodę optymalizacji.

13

Niching mechanisms in evolutionary computations

Kowalczuk Z., Białaszewski T.

International Journal of Applied Mathematics and Computer Science

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2006

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Vol. 16, no 1

59-84

EN

Different types of niching can be used in genetic algorithms (GAs) or evolutionary computations (ECs) to sustain the diversity of the sought optimal solutions and to increase the effectiveness of evolutionary multi-objective optimization solvers. In this paper four schemes of niching are proposed, which are also considered in two versions with respect to the method of invoking: a continuous realization and a periodic one. The characteristics of these mechanisms are discussed, while as their performance and effectiveness are analyzed by considering exemplary multi-objective optimization tasks both of a synthetic and an engineering (FDI) design nature.

14

Evolutionary Multi-Objective Pareto Optimisation of Diagnostic State Observers

Kowalczuk Z., Suchomski P., Białaszewski T.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

689-709

EN

A multi-objective Pareto-optimisation procedure for the design of residual generators which constitute a primary instrument for model-based fault detection and isolation (FDI) in systems of plant monitoring and control is considered. An evolutionary approach to the underlying multi-objective optimisation problem is utilised. The resulting robust observer detector allows for FDI, taking into account the issue of false alarms.