PARAMETRIC OPTIMIZING ANALYSIS OF UNSTEADY STRUCTURES AND VISUALIZATION OF MULTIDIMENSIONAL DATA

2013 ◽  
Vol 04 (supp01) ◽  
pp. 1341004 ◽  
Author(s):  
A. E. BONDAREV ◽  
V. A. GALAKTIONOV
Keyword(s):  
Optimization Problem ◽  
Visual Presentation ◽  
Analytical Form ◽  
Multidimensional Data ◽  
Problem Solution ◽  
Characteristic Parameters ◽  
Approximate Estimation ◽  
Time Structures ◽  
Presentation Methods ◽  
Approximate Dependence

The paper presents an approach to fast approximate estimation of conditions for space-time structures appearing in the flows. The approach is based on combination of optimization problem computation with methods of data visual presentation. The visual presentation methods are applied for analysis of multidimensional array containing discrete result data. Optimization problem solution is implemented by parallel computation in a multitask form. For some cases, the approach allows to obtain for control parameter of considered problem the sought-for approximate dependence on characteristic parameters in a quasi-analytical form.

scholarly journals GENETIC ALGORITHMS FOR MULTIDIMENSIONAL SCALING / GENETINIŲ ALGORITMŲ TAIKYMAS DAUGIAMATĖMS SKALĖMS

2015 ◽  
Vol 7 (3) ◽  
pp. 275-279 ◽  
Author(s):  
Agnė Dzidolikaitė
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Multidimensional Scaling ◽  
Optimization Problem ◽  
Dimensional Space ◽  
Local Solution ◽  
Multidimensional Data ◽  
Global Optimization Problem ◽  
Lower Dimensional Space ◽  
Lower Dimensional

The paper analyzes global optimization problem. In order to solve this problem multidimensional scaling algorithm is combined with genetic algorithm. Using multidimensional scaling we search for multidimensional data projections in a lower-dimensional space and try to keep dissimilarities of the set that we analyze. Using genetic algorithms we can get more than one local solution, but the whole population of optimal points. Different optimal points give different images. Looking at several multidimensional data images an expert can notice some qualities of given multidimensional data. In the paper genetic algorithm is applied for multidimensional scaling and glass data is visualized, and certain qualities are noticed. Analizuojamas globaliojo optimizavimo uždavinys. Jis apibrėžiamas kaip netiesinės tolydžiųjų kintamųjų tikslo funkcijos optimizavimas leistinojoje srityje. Optimizuojant taikomi įvairūs algoritmai. Paprastai taikant tikslius algoritmus randamas tikslus sprendinys, tačiau tai gali trukti labai ilgai. Dažnai norima gauti gerą sprendinį per priimtiną laiko tarpą. Tokiu atveju galimi kiti – euristiniai, algoritmai, kitaip dar vadinami euristikomis. Viena iš euristikų yra genetiniai algoritmai, kopijuojantys gyvojoje gamtoje vykstančią evoliuciją. Sudarant algoritmus naudojami evoliuciniai operatoriai: paveldimumas, mutacija, selekcija ir rekombinacija. Taikant genetinius algoritmus galima rasti pakankamai gerus sprendinius tų uždavinių, kuriems nėra tikslių algoritmų. Genetiniai algoritmai taip pat taikytini vizualizuojant duomenis daugiamačių skalių metodu. Taikant daugiamates skales ieškoma daugiamačių duomenų projekcijų mažesnio skaičiaus matmenų erdvėje siekiant išsaugoti analizuojamos aibės panašumus arba skirtingumus. Taikant genetinius algoritmus gaunamas ne vienas lokalusis sprendinys, o visa optimumų populiacija. Skirtingi optimumai atitinka skirtingus vaizdus. Matydamas kelis daugiamačių duomenų variantus, ekspertas gali įžvelgti daugiau daugiamačių duomenų savybių. Straipsnyje genetinis algoritmas pritaikytas daugiamatėms skalėms. Parodoma, kad daugiamačių skalių algoritmą galima kombinuoti su genetiniu algoritmu ir panaudoti daugiamačiams duomenims vizualizuoti.

A Virtual Bearing Method for Optimal Bearing Placement of Flexible Rotor Systems

2017 ◽  
Author(s):  
Shibing Liu ◽  
Bingen Yang
Keyword(s):  
Optimization Problem ◽  
Optimization Method ◽  
Rotor System ◽  
Problem Solution ◽  
Flexible Rotor ◽  
Rotor Systems ◽  
Real Coded Genetic Algorithm ◽  
Minimum Number ◽  
Distributed Transfer Function ◽  
Flexible Rotor Systems

Flexible multistage rotor systems have a variety of engineering applications. Vibration optimization is important to the improvement of performance and reliability for this type of rotor systems. Filling a technical gap in the literature, this paper presents a virtual bearing method for optimal bearing placement that minimizes the vibration amplitude of a flexible rotor system with a minimum number of bearings. In the development, a distributed transfer function formulation is used to define the optimization problem. Solution of the optimization problem by a real-coded genetic algorithm yields the locations and dynamic coefficients of bearings, by which the prescribed operational requirements for the rotor system are satisfied. A numerical example shows that the proposed optimization method is efficient and accurate, and is useful in preliminary design of a new rotor system with the number of bearings unforeknown.

Combined Analysis and Optimization of Extended Heat Transfer Surfaces

1985 ◽  
Vol 107 (3) ◽  
pp. 527-532 ◽  
Author(s):  
A. N. Hrymak ◽  
G. J. McRae ◽  
A. W. Westerberg
Keyword(s):  
Optimization Problem ◽  
Radiative Heat ◽  
Inequality Constraints ◽  
Finite Element Approximation ◽  
Problem Formulation ◽  
Element Approximation ◽  
Problem Solution ◽  
Radiative Heat Loss ◽  
Equality And Inequality Constraints ◽  
Grid Points

This study presents an efficient numerical method to discover the optimal shape for a fin subject to both convective and radiative heat loss. Problem formulation is a finite element approximation to the conduction equation embedded within and solved simultaneously with the shape optimization problem. The approach handles arbitrary equality and inequality constraints. Grid points move to conform to the fin shape during the problem solution, reducing the number of elements required in the solution.

Application and Benefits of the Virtual Reality Technique for Product Conceptual Design

2010 ◽  
Vol 450 ◽  
pp. 568-571
Author(s):  
Chiuhsiang Joe Lin ◽  
Shiau Feng Lin ◽  
Rou Wen Wang ◽  
Tien Lung Sun ◽  
Chin Jung Chao ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Conceptual Design ◽  
Visual Presentation ◽  
Presentation Methods ◽  
To Receive

Selecting a right way to display the conceptual design results is an important issue for designers. This study evaluated three common computerized visual presentation methods for demonstrating the conceptual ideas of product designs. They are pictures, animations, and image-based VR. After evaluations, this study found that the image-based VR reached the best results of getting the ideas of the conceptual design. It is therefore suggested to use the image-based VR approach if designers wish to receive the most possible advices and feedback, especially in restricted presenting time. The image-based VR approach will help users understand many aspects and considerations of the designer’s conceptual ideas more easily and quickly.

scholarly journals Noninferior Solution Grey Wolf Optimizer with an Independent Local Search Mechanism for Solving Economic Load Dispatch Problems

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2274 ◽  
Author(s):  
Jianzhong Xu ◽  
Fu Yan ◽  
Kumchol Yun ◽  
Lifei Su ◽  
Fengshu Li ◽  
...  
Keyword(s):  
Power Systems ◽  
Local Search ◽  
Optimization Problem ◽  
Search Strategy ◽  
Local Optimum ◽  
Economic Load Dispatch ◽  
Problem Solution ◽  
Main Task ◽  
Grey Wolf ◽  
Local Search Strategy

The economic load dispatch (ELD) problem is a complex optimization problem in power systems. The main task for this optimization problem is to minimize the total fuel cost of generators while also meeting the conditional constraints of valve-point loading effects, prohibited operating zones, and nonsmooth cost functions. In this paper, a novel grey wolf optimization (GWO), abbreviated as NGWO, is proposed to solve the ELD problem by introducing an independent local search strategy and a noninferior solution neighborhood independent local search technique to the original GWO algorithm to achieve the best problem solution. A local search strategy is added to the standard GWO algorithm in the NGWO, which is called GWOI, to search the local neighborhood of the global optimal point in depth and to guarantee a better candidate. In addition, a noninferior solution neighborhood independent local search method is introduced into the GWOI algorithm to find a better solution in the noninferior solution neighborhood and ensure the high probability of jumping out of the local optimum. The feasibility of the proposed NGWO method is verified on five different power systems, and it is compared with other selected methods in terms of the solution quality, convergence rate, and robustness. The compared experimental results indicate that the proposed NGWO method can efficiently solve ELD problems with higher-quality solutions.

Entropy–KEMIRA Approach for MCDM Problem Solution in Human Resources Selection Task

2017 ◽  
Vol 16 (05) ◽  
pp. 1183-1209 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Stanislavas Dadelo ◽  
Natalja Kosareva ◽  
Edmundas Kazimieras Zavadskas
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Optimization Problem ◽  
Evaluation Criteria ◽  
Multiple Criteria Decision Making ◽  
Selection Task ◽  
Life Goals ◽  
Problem Solution ◽  
Criteria Weights ◽  
First Time

Entropy–KEMIRA approach is proposed for criteria ranking and weights determining when solving Multiple Criteria Decision-Making (MCDM) problem in human resources selection task. For the first time the method is applied in the case of three groups of criteria. Weights are calculated by solving optimization problem of maximizing the number of elements, which are “best” according to all three criteria, and minimizing the number of “doubtful” elements. The algorithm of problem solution is presented in the paper. The numerical experiment with three groups of evaluation criteria describing 11 life goals was accomplished.

An Optimization Algorithm Based on Job Shop Scheduling with Fuzzy Goals

2014 ◽  
Vol 912-914 ◽  
pp. 1156-1159
Author(s):  
Qing Ling Dai ◽  
Sheng Bo Zhang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Operating Mode ◽  
Problem Solution ◽  
Improved Genetic Algorithm ◽  
Shop Scheduling ◽  
Delivery Date ◽  
Scheduling Method

The mathematical model was built up for the job shop scheduling problem at first. With following the fuzzy submit time of customer requirement an improved genetic algorithm of fuzzy objective scheduling method was put forward which took the minimum production cost as the objective function. It solved the faults of the chromosomes in genetic algorithm is difficult to accurately express the complex optimization problem solution and determined the more suitable multilayer encoding and operating mode. The simulation results show that this algorithm can be applied to fuzzy object shop scheduling optimization problem, which can ensure the machine's load balance and meet the requirements of the customer delivery date.

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