• International conference on construction engineering and project management
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• 2022.06a
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• pp.196-203
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• 2022

The resource constrained scheduling problem (RCSP) constitutes one of the most challenging problems in Project Management, as it combines multiple parameters, contradicting objectives (project completion within certain deadlines, resource allocation within resource availability margins and with reduced fluctuations), strict constraints (precedence constraints between activities), while its complexity grows with the increase in the number of activities being executed. Due to the large solution space size, this work investigates the application of Genetic Algorithms to approximate the optimal resource alolocation and obtain optimal trade-offs between different project goals. This analysis uses the cost of exceeding the daily resource availability, the cost from the day-by-day resource movement in and out of the site and the cost for using resources day-by-day, to form the objective cost function. The model is applied in different case studies: 1 project consisting of 10 activities, 4 repetitive projects consisting of 40 activities in total and 16 repetitive projects consisting of 160 activities in total, in order to evaluate the effectiveness of the algorithm in different-size solution spaces and under alternative optimization criteria by examining the quality of the solution and the required computational time. The case studies 2 & 3 have been developed by building upon the recurrence of the unit/sub-project (10 activities), meaning that the initial problem is multiplied four and sixteen times respectively. The evaluation results indicate that the proposed model can efficiently provide reliable solutions with respect to the individual goals assigned in every case study regardless of the project scale.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.17-30
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• 1997

In this work we approximate the solution of initialboun-dary value problem using a Galerkin-finite element method for the spatial discretization and Implicit Runge-Kutta method for the spatial discretization and implicit Runge-Kutta methods for the time stepping. To deal with the nonlinear term f(x, t, u), we introduce the well-known extrapolation sheme which was used widely to prove the convergence in $L_2$-norm. We present computational results showing that the optimal order of convergence arising under $L_2$-norm will be preserved in $L_{\infty}$-norm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.42-52
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• 2022

North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.99-104
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• 2024

In the deficiency of an exact solution yielding algorithm, approximate algorithms remain as a solely viable option to the Minimum Linear Arrangement(MinLA) problem of Binary tree. Despite repeated attempts by a number of algorithm on k = 10, only two of them have been successful in yielding the optimal solution of 3,696. This paper therefore proposes an algorithm of O(n) complexity that delivers the exact solution to the binary tree. The proposed algorithm firstly employs an In-order search method by which n = 2^k - 1 number of nodes are assigned with a distinct number. Then it reassigns the number of all nodes that occur on level 2 ≤ 𝑙 ≤ k-2, (k = 5) and 2 ≤ 𝑙 ≤ k-3, (k = 6), including that of child of leaf node. When applied to k=5,6,7, the proposed algorithm has proven Chung[14]'s S^(k)_min=2^k-1+4+S^(k-1)_min+2S^(k-2)_min conjecture and obtained a superior result. Moreover, on the contrary to existing algorithms, the proposed algorithm illustrates a detailed assignment method. Capable of expeditiously obtaining the optimal solution for the binary tree of k > 10, the proposed algorithm could replace the existing approximate algorithms.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.111-118
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• 2015

This paper deals with the routing and wavelength assignment problem (RWAP) that decides the best lightpaths for multiple packet demands for (s,t) in optical communication and assigns the minimum number of wavelengths to given lightpaths. There has been unknown of polynomial-time algorithm to obtain the optimal solution for RWAP. Hence, the RWAP is classified as NP-complete problem and one can obtain the approximate solution in polynomial-time. This paper decides the shortest main and alternate lightpath with same hop count for all (s,t) for given network in advance. When the actual demands of communication for particular multiple packet for (s,t), we decrease the maximum utilized edge into b utilized number using these dual-paths. Then, we put these (s,t) into b-wavelength bins without duplicated edge. This algorithm can be get the optimal solution within O(kn) computational complexity. For two experimental data, the proposed algorithm shows that can be obtain the known optimal solution.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1081-1096
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• 2011

In this paper, a steady axisymmetric MHD flow of two dimensional incompressible fluids is studied under the influence of a uniform transverse magnetic field. The governing equations are reduced to nonlinear boundary value problem by applying the integribility conditions. Optimal Homotopy Asymptotic Method (OHAM) is applied to obtain solution of reduced fourth order nonlinear boundary value problem. For comparison, the same problem is also solved by Variational Iteration Method (VIM).

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.120-131
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• 1997

This paper presents an approximate reanalysis methods of structures based on substructuring for an effective optimization of large-scale structural systems. In most optimal design procedures the analysis of the structure must be repeated many times. In particular, one of the main obstacles in the optimization of structural systems are involved high computational cost and expended long time in the optimization of large-scale structures. The purpose of this paper is to evaluate efficiently the structural behavior of new designs using information from previous ones, without solving basic equations for successive modification in the optimal design. The proposed reanalysis procedure is combined Taylor series expansions which is a local approximation and reduced basis method which is a global approximation based on substructuring. This technique is to choose each of the terms of Taylor series expansions as the basis vector of reduced basis method in substructuring system which is one of the most effective analysis of large -scale structures. Several numerical examples illustrate the effectiveness of the solution process.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.225-228
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• 1992

The purpose of this project is the presentation of new method for selection of a scalar control of linear time-periodic system. The approach has been proposed by Radziszewski and Zaleski [4] and utilizes the quadratic form of Lyapunov function. The system under consideration is assigned either in closed-loop state or in modal variables as in Calico, Wiesel [1]. The case of scalar control is considered, the gain matrix being assumed to be at worst periodic with the system period T, each element being represented by a Fourier series. As the optimal gain matrix we consider the matrix ensuring the minimum value of the larger real part of the two Poincare exponents of the system. The method, based on two-step optimization procedure, allows to find the approximate optimal gain matrix. At present state of art determination of the gain matrix for this case has been done by systematic numerical search procedure, at each step of which the Floquet solution must be found.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.4
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• pp.337-350
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• 2014

In this paper, we consider discontinuous Galerkin finite element methods with interior penalty term to approximate the solution of nonlinear parabolic problems with mixed boundary conditions. We construct the finite element spaces of the piecewise polynomials on which we define fully discrete discontinuous Galerkin approximations using the Crank-Nicolson method. To analyze the error estimates, we construct an appropriate projection which allows us to obtain the optimal order of a priori ${\ell}^{\infty}(L^2)$ error estimates of discontinuous Galerkin approximations in both spatial and temporal directions.

• East Asian mathematical journal
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• v.32 no.1
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• pp.101-115
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• 2016

In this paper, we consider a semi-discrete mixed discontinuous Galerkin method with an interior penalty to approximate the solution of parabolic problems. We define an auxiliary projection to analyze the error estimate and obtain optimal error estimates in $L^{\infty}(L^2)$ for the primary variable u, optimal error estimates in $L^2(L^2)$ for ut, and suboptimal error estimates in $L^{\infty}(L^2)$ for the flux variable ${\sigma}$.