• 호남수학학술지
• /
• 제29권1호
• /
• pp.83-100
• /
• 2007

Normality is one of the most common assumptions made in sampling and statistical inference procedures without suffering from lack of attention. Its results may lead to an invalid conclusion. We present several testing procedures that can be used to evaluate the effects of departure from normality using concrete examples by hand or with the aid of Minitab. The goal is to influence prospective teachers in order to learn statistical concepts and techniques for testing normality on the basis of the didactical theory.

• Journal of Electrical Engineering and Technology
• /
• 제9권2호
• /
• pp.423-432
• /
• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).

• International Journal of Computer Science & Network Security
• /
• 제21권12호
• /
• pp.175-182
• /
• 2021

Deadlock is a situation in which two or more processes competing for resources are waiting for the others to finish, and neither ever does. There are two different forms of systems, multi-unit and single-unit resource systems. The difference is the number of instances (or units) of each type of resource. Deadlock problem can be modeled as a constrained combinatorial problem that seeks to find a possible scheduling for the processes through which the system can avoid entering a deadlock state. To solve deadlock problem, several algorithms and techniques have been introduced, but the use of metaheuristics is one of the powerful methods to solve it. Genetic algorithms have been effective in solving many optimization issues, including deadlock Problem. In this paper, an improved parallel framework of the genetic algorithm is introduced and adapted effectively and efficiently to deadlock problem. The proposed modified method is implemented in java and tested on a specific dataset. The experiment shows that proposed approach can produce optimal solutions in terms of burst time and the number of feasible solutions in each advanced generation. Further, the proposed approach enables all types of crossovers to work with high performance.

• Structural Engineering and Mechanics
• /
• 제55권6호
• /
• pp.1121-1137
• /
• 2015

High powered computers and engineering computer systems allow designers to routinely simulate complex physical phenomena. The presented work deals with the analysis of two finite element method optimization techniques (First Order Method-FOM and Subproblem Approximation Method-SAM) implemented in the individual Design Optimization module in the Ansys software to analyze the behavior of real problems. A design optimization is a difficult mathematical process, intended to find the minimum or maximum of an objective function, which is mostly based on iterative procedure. Using optimization techniques in engineering designs requires detailed knowledge of the analyzed problem but also an ability to select the appropriate optimization method. The methods embedded in advanced computer software are based on different optimization techniques and their efficiency is significantly influenced by the specific character of a problem. The efficiency, robustness and accuracy of the methods are studied through strictly convex two-dimensional optimization problem, which is represented by volume minimization of two bars' plane frame structure subjected to maximal vertical displacement limit. Advantages and disadvantages of the methods are described and some practical tips provided which could be beneficial in any efficient engineering design by using an optimization method.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
• /
• pp.979-986
• /
• 2002

Constraint Programming is an appealing technology for modeling and solving various real-world problems. and metaheuristic is the most successful technique available for solving large real-world vehicle routing problems. Constraint Programming and metaheuristic are complementary to each other. This paper describes how iterative improvement techniques can be used in a Constraint Programming framework(LOG Solver and ILOG Dispatcher) for Vehicle Routing Problem. As local search gets trapped in local solution, the improvement techniques are used in conjunction with metaheuristic method.

• 한국과학교육학회지
• /
• 제11권2호
• /
• pp.87-101
• /
• 1991

Science-Technology-Society curricula have been developed in several countries for the last 20 years. Those curricula were focused on social aspects of science, i.e., value-laden knowledge and scientific enterprise, and society-related scientific and technological issues, i.e., energy, pollution, natural resources. The major teaching models employed in those curricula were problem solving and decision making, which required the following teaching techniques: teacher as a manager, small group discussion, controversy as a motivational force for substantive learning, and sufficient factual information into the discussion. Further researches are to be made to ascertain whether or not the expectations of the curricula might be realized in practice. It was shown that most Korean biology teachers considered the STS-related goal of science education as more important than the other goals. Based upon the findings, some recommendations for development of Korean STS curriculum were made as follows: 1. The contents of the STS curricula are to be organized with the integrated mode; 2. The major teaching models throughout the contents are to be problem solving and decision making. These are considered to provide students with the opportunities to involve in debates on practical issues and to draw consensus from them; 3. Some degree of flexibility should be provided on teachers' implementation of the curriculum in terms of contents, teaching techniques etc.; 4. To increase the practicality of the curriculum, teachers should be involved in the development of the curriculum and the relevant research; and 5. Contents to be included in STS curriculum were suggested by some science educators, but the more systematic study is required in this respect.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• 제3권1호
• /
• pp.31-41
• /
• 1999

We investigate some techniques of iterative refinement of solutions of a nonsingular system Ax = b with A partitioned into blocks using only single precision arithmetic. We prove that iterative refinement improves a blockwise measure of backward stability. Some applications of the results for the least squares problem (LS) will be also considered.

• 한국산학기술학회:학술대회논문집
• /
• 한국산학기술학회 2011년도 춘계학술논문집 2부
• /
• pp.635-637
• /
• 2011

In this paper, to solve the problem of contradiction is proposed new RPS-TRIZ. RPS-TRIZ is evolved from TRIZ technique which 6SC of existing and tries to adopt the strong point of the Q-TRIZ techniques. RPS-TRIZ can be used to improve problems in the field more quickly and easily.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 2003년도 추계학술대회 및 정기총회
• /
• pp.89-92
• /
• 2003

It is often that a large-scale linear programming(LP) problem may contain many constraints which are redundant or cause infeasibility on account of inefficient formulation or some errors in data input. Presolving or preprocessing is a series of operations which removes the underlying redundancy or detects infeasibility in the given LP problem. It is essential for the speedup of an LP system solving large-scale problems to implement presolving techniques. For the recovery of an optimal solution for the original problem from an optimal solution for the presolved problem, a special procedure, so called postsolving, must be applied. In this paper, we present how a postsolving procedure is constructed and implemented in LPABO, a interior-point based LP system. Briefly, all presolving processes are logged in a data structure in LPABO, and after the end of the solution method an optimal solution for the original problem is obtained by tracing the logs. In each stage of the postsolving procedure, the optimality of intermediate solutions is maintained. We tested our postsolving procedure on Netlib, Gondzio and Kennington LP data sets, and concluded that the computational burden of the procedure is relatively negligible compared with the total solving time.

• 한국디지털정책학회:학술대회논문집
• /
• 한국디지털정책학회 2004년도 춘계학술대회
• /
• pp.517-524
• /
• 2004

교육은 끊임없는 대화로 이루어지므로 웹을 통한 온라인 학습 시스템에서도 사회적 상호작용이 활발히 일어날 수 있는 환경을 만드는것이 필수적이다. 이에 본 연구에서는 인터넷을 활용한 효과적인 문제 해결학습을 위해 플랫폼 독립적인 상호작용도구를 이용하는 웹 기반의 문제 해결학습시스템을 개발하였다. 문제 해결 모델은 학교 현장에서 학습효과를 증진시키기 위한 문제 해결 학습 모형으로 전문가 모둠 활동과 향상점수를 활용하여 학습에 긍정적인 영향을 주는 것으로 평가되고 있다. 본 연구에서는 문제해결을 위한 핵심적인 기법이라고 할 수 있는 문제분석과 결정분석 두 가지 기법을 중심으로 학습 프로그램 내용을 조직하고 지원하는 여러 가지 기능을 개발하였다.