• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.613-624
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• 2021

This paper analyzes the relationship between income distribution and energy consumption from a Pareto optimal approach. For this purpose, the causality relationship between electricity consumption per capita (kWh) with respect to country groups and energy consumption per capita (kg of oil equivalent) along with gross domestic product per capita was analyzed. In addition to this purpose, a Pareto analysis was conducted to determine the countries with the highest per capita national income, how much of the world total energy they consume, and whether the law of power in the energy and electricity markets exists. Finally, the impact of official development assistance provided to low-income countries by high-income countries on the low-income countries' electricity and energy consumption was analyzed. In other words, it was questioned whether pareto redistribution policies serve the purpose or not. The Engle-Granger causality approach was used in the analysis of the causality relationship between variables. Our analysis indicated that, first, the energy data of the country groups may be inadequate in revealing income inequalities. Second, the existence of Pareto law of power and global income inequality can be explained based on energy data. Finally, Pareto optimal redistribution policies to eliminate income inequality remain inadequate in practice.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.499-505
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• 2004

The Pareto diagram analysis of the experimental data by the two level orthogonal arrays has been used widely in practice since it is a graphical, quick and easy method to analyze experimental results, which does not use the analysis of variance to screen significant effects. For the analysis of the experimental data by $L_{18}(2 \times 3^7)$ orthogonal array, Park(1996) proposed Pareto ANOVA in which the size of effects is defined by the mean squares of effects and the Pareto principle is used. In this paper, a new approach of the Pareto diagram analysis of the experimental data by $L_{18}(2 \times 3^7)$ orthogonal array is proposed. The main idea is to partition the size of three level effects by that of linear and quadratic orthogonal contrasts of those effects.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.569-575
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• 2018

Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.71-80
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• 2017

Software reliability is one of the most elementary and important problems in software development In order to find the software failure occurrence, the instantaneous failure rate function in the Poisson process can have a constant, incremental or decreasing tendency independently of the failure time. In this study, we compared the reliability performance of the software reliability model using the parameters of Pareto life distribution with the intensity decreasing pattern and the shape parameter of Erlang life distribution with the intensity increasing and decreasing pattern in the software product testing. In order to identify the software failure environment, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, we compare and evaluate software reliability by applying software failure time data. The reliability of the Erlang and Pareto life models is shown to be higher than that of the Pareto lifetime distribution model when the shape parameter is higher and the Erlang model is more reliable when the shape parameter is higher. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing basic knowledge using software failure analysis.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1435-1451
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• 2011

In this paper the estimation of the parameters as well as survival and hazard functions are presented for the two-parameter Pareto distribution by using Bayesian and non-Bayesian approaches under upper record values. Maximum likelihood estimation (MLE) and interval estimation are derived for the parameters. Bayes estimators of reliability performances are obtained under symmetric (Squared error) and asymmetric (Linex and general entropy (GE)) losses, when two parameters have discrete and continuous priors, respectively. Finally, two numerical examples with real data set and simulated data, are presented to illustrate the proposed method. An algorithm is introduced to generate records data, then a simulation study is performed and different estimates results are compared.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• International Journal of Fluid Machinery and Systems
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• v.3 no.2
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• pp.150-159
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• 2010

Laidback fan shaped film-cooling hole is formulated numerically and optimized with the help of three-dimensional numerical analysis, surrogate methods, and the multi-objective evolutionary algorithm. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by four geometric design variables, the injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole, to maximize the film-cooling effectiveness compromising with the aerodynamic loss. The objective function values are numerically evaluated through Reynolds- averaged Navier-Stokes analysis at the designs that are selected through the Latin hypercube sampling method. Using these numerical simulation results, the Response Surface Approximation model are constructed for each objective function and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto optimal front. The clustered points from Pareto optimal front were evaluated by flow analysis. These designs give enhanced objective function values in comparison with the experimental designs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.141-148
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• 2000

In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary optimization techniques. This approach is applied to some mathematical examples and structural optimization problems.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.10
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• pp.245-250
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• 2019

The use of NAND flash memory has increased rapidly due to the development of mobile fields. However, NAND flash memory has a limited lifespan, so studies are underway to predict its lifespan. Workload is one of the factors that significantly affect the life of NAND flash memory, and workload analysis studies in mobile environments are insufficient. In this paper, we analyze the distribution of workload in the mobile environment by collecting traces generated by using Android-based smartphones. The collected traces can be divided into three groups of hotness. Also they are distributed in the form of heavy tails. We fit this to the Pareto, Lognormal, and Weibull distributions, and Traces are closest to the Pareto distribution.

• Advances in Computational Design
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• v.6 no.1
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• pp.31-42
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• 2021

This research aims to demonstrate the optimal geometrical design of splayed multiple cross-sectional pin fin heat sinks (SMCSPFHS), which are a type of side-inlet-side-outlet heat sink (SISOHS). The optimiser strength Pareto evolutionary algorithm2 (SPEA2)is employed to explore a set of Pareto optimalsolutions. Objective functions are the fan pumping power and junction temperature. Function evaluations can be accomplished using computational fluid dynamics(CFD) analysis. Design variablesinclude pin cross-sectional areas, the number of fins, fin pitch, thickness of heatsink base, inlet air speed, fin heights, and fin orientations with respect to the base. Design constraints are defined in such a way as to make a heat sink usable and easy to manufacture. The optimum results obtained from SPEA2 are compared with the straight pin fin design results obtained from hybrid population-based incremental learning and differential evolution (PBIL-DE), SPEA2, and an unrestricted population size evolutionary multiobjective optimisation algorithm (UPSEMOA). The results indicate that the splayed pin-fin design using SPEA2 issuperiorto those reported in the literature.