Wyniki wyszukiwania - BazTech

1

Shape optimization of the muffler shield with regard to strength properties

Jarosz Joachim, Długosz Adam

Engineering Transactions

|

2023

|

Vol. 71, iss. 3

351--366

EN

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.

2

A Survey on multi-objective based parameter optimization for deep learning

Chakraborty Mrittika, Pal Wreetbhas, Bandyopadhyay Sanghamitra, Maulik Ujjwal

Computer Science

|

2023

|

T. 24 (3)

327--359

EN

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.

3

Multi-objective optimization of PCM-fin structure for staggered Li-ion battery packs

Qiu Chenghui, Wu Chongtian, Yuan Xiaolu, Wu Linxu, Yang Jiaming, Shi Hong

Bulletin of the Polish Academy of Sciences. Technical Sciences

|

2023

|

Vol. 71, nr 4

art. no. e145677

EN

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.

4

A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor

Knypiński Łukasz

Bulletin of the Polish Academy of Sciences. Technical Sciences

|

2023

|

Vol. 71, nr 1

art. no. e144586

EN

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.

5

Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm

Yilmaz Mehmet, Dede Tayfun, Grzywiński Maksym

Budownictwo o Zoptymalizowanym Potencjale Energetycznym

|

2023

|

Vol. 12

79--86

EN

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.

6

A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid

Khoshayand Hossein Ali, Wattanapongsakorn Naruemon, Mahdavian Mehdi, Ganji Ehsan

Archives of Electrical Engineering

|

2023

|

Vol. 72, nr 1

253--271

EN

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.

7

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

|

2022

|

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.

8

Applying optimization techniques on cold-formed C-channel section under bending

El-Lafy Heba F., Elgendi Elbadr O., Morsy Alaa M.

International Journal of Applied Mechanics and Engineering

|

2022

|

Vol. 27, no. 4

52--65

EN

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.

9

Optimizing the Multi-Level Location-Assignment Problem in Queue Networks Using a Multi-Objective Optimization Approach

Syah Rahmad, Elveny Marischa, Soerjati Enni, Guerrero John William Grimaldo, Jowad Rawya Read, Suksatan Wanich, Aravindhan Surendar, Voronkova Olga Yuryevna, Mavaluru Dinesh

Foundations of Computing and Decision Sciences

|

2022

|

Vol. 47, No. 2

177--192

EN

Using hubs in distribution networks is an efficient approach. In this paper, a model for the location-allocation problem is designed within the framework of the queuing network in which services have several levels, and customers must go through these levels to complete the service. The purpose of the model is to locate an appropriate number of facilities among potential locations and allocate customers. The model is presented as a multi-objective nonlinear mixed-integer programming model. The objective functions include the summation of the customer and the waiting time in the system and the waiting time in the system and minimizing the maximum possibility of unemployment in the facility. To solve the model, the technique of accurate solution of the epsilon constraint method is used for multi-objective optimization, and Pareto solutions of the problem will be calculated. Moreover, the sensitivity analysis of the problem is performed, and the results demonstrate sensitivity to customer demand rate. Based on the results obtained, it can be concluded that the proposed model is able to greatly summate the customer and the waiting time in the system and reduce the maximum probability of unemployment at several levels of all facilities. The model can also be further developed by choosing vehicles for each customer.

10

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Syah Rahmad, Nasution Mahyuddin M., Shol Vladimir Vladimirovich, Kireeva Natalia, Jalil Abduladheem Turki, Chen Tzu-Chia, Aravindhan Surendar, Abood Emad Salaam, Alkaim Ayad F.

Foundations of Computing and Decision Sciences

|

2022

|

Vol. 47, No. 2

193--207

EN

Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization's priorities, which can be environmental or financial.

11

Experimental and numerical investigation on the multi-optimization of reinforcing the side members of the vehicle structure

Zahedan Nima, Ahmadi Hamed, Liaghat Gholam Hossein

Archives of Civil and Mechanical Engineering

|

2022

|

Vol. 22, no. 1

art. no. e25, 2022

EN

The aim of this study is to investigate the improvement in the strength of a top-hat profile hollow-section beam used in a vehicle structure by attaching different shapes of internal reinforcements. The base structure of the beam was first considered as a hat-shape structure which was jointed to a flat plate using spot-welds. Three types of sheet metal reinforcements were formed and attached inside the beam’s structure. Then, they were tested experimentally under low-velocity lateral impact. Also, a numerical simulation is being developed using LS-DYNA explicit code and validated using experimental data. Valid numerical configuration is used to conduct an optimization study on cross-sectional shape of the internal reinforcing component. Optimizations are carried out using single- and multi-objective methods based on Genetic Algorithm approach and the suggested optimum solutions are compared with experimental results. Moreover, to discuss the feasibility of applied reinforcements on side section of a vehicle’s body-in-white, a realistic side-pole crash test is simulated using a validated vehicle model and performance of improved chassis is compared with basic model and results are presented, discussed and commented upon.

12

Multi-objective evolutionary algorithms and some of their applications in reliability

Coello Coello Carlos A., Castillo Tapia Ma Guadalupe

Safety and Reliability of Systems and Processes

|

2021

|

Summer Safety and Reliability Seminar 2021

45--57

EN

Multi-objective optimization has become increasingly important, mainly because many real-world problems are multi-objective in nature. The complexity of many of such problems has made necessary the use of metaheuristics. From them, the use of multi-objective evolutionary algorithms has become very popular mainly because of their ease of use and flexibility. In this chapter, we provide a short review of multi-objective evolutionary algorithms and some of their applications in reliability. In the final part of the chapter, some possible paths for future research in this area are also discussed.

13

Multi-objective optimization of process parameters in cold forging minimizing risk of crack and forging energy

Kitayama Satoshi, Kadoya Shimon, Takano Masahiro, Kobayashi Akio

Archives of Civil and Mechanical Engineering

|

2021

|

Vol. 21, no. 3

795--806

EN

In this paper, a typical cold forging process using spring-held die is considered, in which the process parameters such as stiffness of spring, the initial loads and the punch speed are conventionally adjusted by the trial-and-error method for high product quality. The target product has the earing, around which the crack is often observed by the conventional process parameters. To avoid the crack around the earing, the process parameters optimization is performed through numerical simulation using DEFORM3D, in which two objective functions are considered. The risk of crack is numerically evaluated and is minimized, whereas the total forging energy using the load-stroke diagram is also minimized. Therefore, the multi-objective design optimization is performed. The numerical simulation is so intensive that sequential approximate optimization using radial basis function network is adopted to identify the pareto-frontier between the objectives with a small number of simulations. Compared with the product using the conventional process parameters, the optimal process parameters can reduce both the risk of crack and the total forging energy. In addition, the flow lines along the product shape can be obtained by using the optimal process parameters. Based on the numerical result, the experiment using the mechanical press (IST100W, ITO) is carried out. No crack is observed in the experiment, and then the validity of the proposed approach is confirmed.

14

Crashworthiness-based multi-objective integrated optimization of electric vehicle chassis frame

Wang Shuang, Wang Dengfeng

Archives of Civil and Mechanical Engineering

|

2021

|

Vol. 21, no. 3

303--320

EN

Chassis frame of electric vehicle contains several thin-walled tube structures that can provide an important component for installing the power unit and supporting the body in white of vehicle. Thus, design a chassis frame is a multi-objective optimization and multi-parameter problem. To address it, the contributions of design variables to the performance indicators of chassis frame are studied first, and obtained the optimal design variables. The effects of the design parameters on the objective responses are analyzed based on a polynomial response surface model. Moreover, to determine optimal solution between the conflicting performance indicators of the chassis frame, an integrated approach based on lightweight and crashworthiness is presented to analysis the performance and determine the Pareto fronts. In addition, the optimal solution is acquired from the Pareto fronts by the grey relational analysis and game theory. Experiments corresponding to the numerical analysis are performed to verify the feasibility of the optimized strategy and the performance of the optimized chassis frame structure. Results show that according to the optimal parameters of chassis frame, the lightweight performance can be improved significantly, while the linear performance and crashworthiness performance of chassis frame are ensured.

15

Automatic generation of high performance morphological ﬁlters to ﬁx missing data in depth images on real-time embedded systems for visually impaired people

Dourado Antonio Miguel Batista, Pedrino Emerson Carlos

Przegląd Elektrotechniczny

|

2020

|

R. 96, nr 1

113--117

EN

The paper presents an evolutionary multi-objective approach to automatically generate morphological ﬁlters to solve unknown distances areas, found in depth images used by real-time embedded systems for visually impaired people, and to prevent accidents. It was used Cartesian Genetic Programming as base for the NSGAII multi-objective optimization algorithm proposed to optimize two objectives: low error rates for quality x low complexity for speed. Results showed this approach was able to deliver feasible solutions with good quality and speed to be used in real-time systems.

PL

W artykule zaprezentowano metodę ewolucyjną do automatycznego generowania morfologicznego ﬁltru do określania brakujących danych w obrazach ludzi otrzymywanych on-line. Użyto programu Cartesian Genetic do optymalizacji algorytmu. Zastosowane rozwiązanie umożliwiało dostarczanie poprawę szybkości o dokładności przetwarzania obrazu.

16

A fuzzy approach to multi-objective mixed integer linear programming model for multi-echelon closed-loop supply chain with multi-product multi-time-period

Akin Bas Sema, Ahlatcioglu Ozkok Beyza

Operations Research and Decisions

|

2020

|

Vol. 30, No. 1

25--46

EN

By the green point of view, supply chain management (SCM), which contains supplier and location selection, production, distribution, and inventory decisions, is an important subject being examined in recent years by both practitioners and academicians. In this paper, the closed-loop supply chain (CLSC) network that can be mutually agreed by meeting at the level of common satisfaction of conflicting objectives is designed. We construct a multi-objective mixed-integer linear programming (MOMILP) model that allows decision-makers to more effectively manage firms’ closed-loop green supply chain (SC). An ecological perspective is brought by carrying out the recycling, remanufacturing and destruction to SCM in our proposed model. Maximize the rating of the regions in which they are located, minimize total cost and carbon footprint are considered as the objectives of the model. By constructing our model, the focus of customer satisfaction is met, as well as the production, location of facilities and order allocation are decided, and we also carry out the inventory control of warehouses. In our multi-product multi-component multi-time-period model, the solution is obtained with a fuzzy approach by using the min operator of Zimmermann. To illustrate the model, we provide a practical case study, and an optimal result containing a preferable level of satisfaction to the decision-maker is obtained.

17

Single spiking neuron multi-objective optimization for pattern classification

Juarez-Santini Carlos, Ornelas-Rodriguez Manuel, Soria-Alcaraz Jorge Alberto, Rojas-Domínguez Alfonso, Puga-Soberanes Hector J., Espinal Andrés, Rostro-Gonzalez Horacio

Journal of Automation Mobile Robotics and Intelligent Systems

|

2020

|

Vol. 14, No. 1

73--80

EN

As neuron models become more plausible, fewer computing units may be required to solve some problems; such as static pattern classification. Herein, this problem is solved by using a single spiking neuron with rate coding scheme. The spiking neuron is trained by a variant of Multi-objective Particle Swarm Optimization algorithm known as OMOPSO. There were carried out two kind of experiments: the first one deals with neuron trained by maximizing the inter distance of mean firing rates among classes and minimizing standard deviation of the intra firing rate of each class; the second one deals with dimension reduction of input vector besides of neuron training. The results of two kind of experiments are statistically analyzed and compared again a Mono-objective optimization version which uses a fitness function as a weighted sum of objectives.

18

Bi-objective routing in a dynamic network: An application to maritime logistics

Maskooki Alaleh, Nikulin Yury

Control and Cybernetics

|

2020

|

Vol. 49, No. 2

211--232

EN

A bi-objectiveMILP model for optimal routing in a dynamic network with moving targets (nodes) is developed, where all targets are not necessarily visited. Hence, our problem extends the moving target travelling salesman problem. The two objectives aim at finding the sequence of targets visited in a given time horizon by minimizing the total travel distance and maximizing the number of targets visited. Due to a huge number of binary variables, such a problem often becomes intractable in the real life cases. To reduce the computational burden, we introduce a measure of traffic density, based on which we propose a time horizon splitting heuristics. In a real-world case study of greenhouse gas emissions control, using Automatic Identification System data related to the locations of ships navigating in the Gulf of Finland, we evaluate the performance of the proposed method. Different splitting scenarios are analysed numerically. Even in the cases of a moderate scale, the results show that near-efficient values for the two objectives can be obtained by our splitting approach with a drastic decrease in computational time compared to the exact MILP method. A linear value function is introduced to compare the Pareto solutions obtained by different splitting scenarios. Given our results, we expect that the present study is valuable in logistic applications, specifically maritime management services and autonomous navigation.

19

The algorithm of multi-objective optimization of PM synchronous motors

Knypiński Łukasz, Nowak Lech

Przegląd Elektrotechniczny

|

2019

|

R. 95, nr 4

242--245

EN

This paper presents multi-objective algorithm for optimal designing of permanent magnet synchronous motors. The special attention is paid on the formulation the optimization problem, especially on the correct selection of the partial criteria which constitute multi-objective function and constraints. It is pointed out that connection of multimodal parameter (cogging torque) and unimodal parameter (electromagnetic torque) in one multi-objective compromise function can lead to erroneous operation of optimization algorithm. Therefore, decomposition of the optimization task into two-level is proposed. The optimization calculation has been executed for permanent magnet synchronous motor structure with hybrid excitation system.

PL

W artykule przedstawiono algorytm do optymalizacji magnetoelektrycznych silników synchronicznych. Przedstawiono rozważania dotyczące poprawnego formułowania kompromisowych funkcji celu, w szczególności odpowiedniego doboru kryteriów cząstkowych. Wykazano, że włączenie do kompromisowej funkcji jednocześnie członu reprezentującego elektromagnetyczny moment użyteczny i moment zaczepowy może prowadzić do błędnego działania algorytmu optymalizacji. Zaproponowano dekompozycję zadania optymalizacji na dwa etapy. Przedstawiono i omówiono wybrane wyniki obliczeń optymalizacyjnych dla magnetoelektrycznego silnika synchronicznego z hybrydowym układem wzbudzenia.

20

Automated optimal design of wells for electromagnetic cell stimulation

Di Barba Paolo, Fassina Lorenzo, Magenes Giovanni, Mognaschi Maria Evelina

Przegląd Elektrotechniczny

|

2019

|

R. 95, nr 5

1--4

EN

In the paper, a device for in vitro electromagnetic stimulation of cells at low frequency (75 Hz) is considered. In particular, shape and position of a well-plate are identified in order to obtain a homogeneous stimulation and to maximize the space allotted to cell culture. To this end, the BiMO and  -BiMO optimization algorithms, which have shown good performances in multi-objective optimization of electromagnetic devices, are applied.

PL

W artykule opisano urządzenie do elektromagnetycznej stymulacji komórek metodą in vitro z wykorzystaniem sygnału o niskiej częstotliwości (75 Hz). W szczególności rozważane były kształt i położenie płytki do hodowli komórkowej w celu uzyskania jednorodnej stymulacji i maksymalizacji przestrzeni obejmującej hodowlę komórkową. W tym celu zastosowano algorytmy optymalizacji BiMO i  -BiMO, które umożliwiły optymalizację wielokryterialną urządzeń elektromagnetycznych.