• East Asian mathematical journal
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• v.32 no.4
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• pp.565-587
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• 2016

The purpose of this study was to analyze the understanding of the meaning of fraction division and fraction division algorithm of elementary mathematical gifted students through the process of problem posing and solving activities. For this goal, students were asked to pose more than two real-world problems with respect to the fraction division of ${\frac{3}{4}}{\div}{\frac{2}{3}}$, and to explain the validity of the operation ${\frac{3}{4}}{\div}{\frac{2}{3}}={\frac{3}{4}}{\times}{\frac{3}{2}}$ in the process of solving the posed problems. As the results, although the gifted students posed more word problems in the 'inverse of multiplication' and 'inverse of a cartesian product' situations compared to the general students and pre-service elementary teachers in the previous researches, most of them also preferred to understanding the meaning of fractional division in the 'measurement division' situation. Handling the fractional division by converting it into the division of natural numbers through reduction to a common denominator in the 'measurement division', they showed the poor understanding of the meaning of multiplication by the reciprocal of divisor in the fraction division algorithm. So we suggest following: First, instruction on fraction division based on various problem situations is necessary. Second, eliciting fractional division algorithm in partitive division situation is strongly recommended for helping students understand the meaning of the reciprocal of divisor. Third, it is necessary to incorporate real-world problem posing tasks into elementary mathematics classroom for fostering mathematical creativity as well as problem solving ability.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.262-269
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involved reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constructs. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model computational experiments using a commercial genetic algorithm based optimizer. The results show that the real size problems we encountered can be solved In reasonable time

• Journal of The Korean Association of Information Education
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• v.17 no.3
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• pp.317-327
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• 2013

Algorithm education that become at the base of thinking is emphasized from primary school. However, It is difficult to understand algorithm in elementary school students level. In this research, it considered curriculum that can teach universally to elementary school students by solution plan of problem. So we chose Scratch program with education data, because it is verified the effect in education of algorithm, and easy to control among EPL (Education Programming Language). It was composed curriculum so that interaction is accomplished through group activities to coincide in various level of students, and approached to the problem-solving center to emphasize important thinking process in algorithm education, and got educational value in relevant level of each student. According to validation of expert groups and surveys, we concluded the curriculum that is appropriate. The curriculum proposed in this paper can help to enhance the problem solving ability and the creativity.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.424-431
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• 2001

This paper is concerned with the unconstrained two-dimensional cutting problem of cutting small rectangles (products), each of which has its own profit and size, from a large rectangle (material) to maximize the profit-sum of products. Since this problem is used as a sub-problem to generate a cutting pattern in the algorithms for the two-dimensional cutting stock problem, most of researches for the two-dimensional cutting stock problem have been concentrated on solving this sub-problem more efficiently. This paper improves Hifi and Zissimopoulos's recursive algorithm, which is known as the most efficient exact algorithm, by applying newly proposed upper bound and searching strategy. The experimental results show that the proposed algorithm has been improved significantly in the computational amount of time as compared with the Hifi and Zissimopulos's algorithm.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.739-748
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• 2007

The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

• Korean Management Science Review
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• v.23 no.2
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• pp.161-174
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• 2006

In this paper, we consider a network optimization problem arising from the deployment of BcN access network. BcN convergence services requires that access networks satisfy QoS meausres. BcN services have two types of traffics : stream traffic and elastic traffic. Stream traffic uses blocking probability as a QoS measure, while elastic traffic uses delay factor as a QoS measure. Incorporating the QoS requirements, we formulate the problem as a nonlinear mixed-integer Programming model. The Proposed model seeks to find a minimum cost dimensioning solution, while satisfying the QoS requirement. We propose two local search heuristic algorithms for solving the problem, and develop a network design system that implements the developed heuristic algorithms. We demonstrate the computational efficacy of the proposed algorithm by solving a realistic network design problem.

• Coupled systems mechanics
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• v.1 no.1
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• pp.99-113
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• 2012

We present a monolithic semi-implicit algorithm for solving fluid-structure interaction problem at small structural displacements. The algorithm uses one global mesh for the fluid-structure domain obtained by gluing the fluid and structure meshes which are matching on the interface. The continuity of velocity at the interface is automatically satisfied and the continuity of stress does not appear explicitly in the global weak form due to the action and reaction principle. At each time step, we have to solve a monolithic system of unknowns velocity and pressure defined on the global fluid-structure domain. Numerical results are presented.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.430-439
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• 2019

The CNN (convolutional neural network) based single degradation restoration method shows outstanding performance yet is tailored on solving a specific degradation type. In this paper, we present an algorithm of multi-degradation classification and restoration. We utilize the CNN based algorithm for solving image degradation classification problem using pre-trained Inception-v3 network. In addition, we use the existing CNN based algorithms for solving particular image degradation problems. We identity the restoration order of multi-degraded images empirically and compare with the non-reference image quality assessment score based on CNN. We use the restoration order to implement the algorithm. The experimental results show that the proposed algorithm can solve multi-degradation problem.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.802-809
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• 2005

A hybrid genetic algorithm is proposed for the problem of generating laser torch paths to cut a stock plate nested with free-formed parts each having a set of sub-parts. In the problem, the total unproductive travel distance of the torch is minimized. The problem is shown to be formulated as a special case of the standard travelling salesman problem. The hybrid genetic algorithm for solving the problem is hierarchically structured: First, it uses a genetic algorithm to find the cutting path f3r the parts and then, based on the obtained cutting path, sequence of sub-parts and their piercing locations are optimally determined by using a combined genetic and heuristic algorithms. This process is repeated until any progress in the total unproductive travel distance is not achieved. Computational results are provided to illustrate the validity of the proposed algorithm.

• The Journal of Information Systems
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• v.17 no.3
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• pp.39-58
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• 2008

Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.