• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.149-159
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• 2009

In this paper, we introduce some approximate optimal solutions and an augmented Lagrangian function in nonlinear programming, establish dual function and dual problem based on the augmented Lagrangian function, discuss the relationship between the approximate optimal solutions of augmented Lagrangian problem and that of primal problem, obtain approximate KKT necessary optimality condition of the augmented Lagrangian problem, prove that the approximate stationary points of augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.248-256
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• 2005

In this paper, we compare two EOQ based inventory models under total cost minimization and profit maximization to investigate the difference in the optimal solutions. First of all, optimal solutions for both models through geometric programming (GP) techniques are found considering production (lot sizing) as well as marketing (pricing) decisions. An investigation of the effects of the changes in the optimal solutions according to varied parameters is performed by studying optimality conditions as well as by performing numerical analysis. We then conduct comparative analysis between the models to show the relationships between the optimal solutions of the models where certain conditions in the cost per unit and the demand per unit time are given. Several interesting economic implications and managerial insights are observed from this analysis.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.

• Bulletin of the Korean Mathematical Society
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• v.55 no.3
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• pp.749-762
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• 2018

In this paper, the new optimal perturbation iteration method has been applied to solve the generalized regularized long wave equation. Comparing the new analytic approximate solutions with the known exact solutions reveals that the proposed technique is extremely accurate and effective in solving nonlinear wave equations. We also show that,unlike many other methods in literature, this method converges rapidly to exact solutions at lower order of approximations.

• Nonlinear Functional Analysis and Applications
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• v.26 no.4
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• pp.781-792
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• 2021

In this paper, we study well-posed problems and variational inequalities in locally convex Hausdorff topological vector spaces. The necessary and sufficient conditions are obtained for the existence of solutions of variational inequality problems and quasi variational inequalities even when the underlying set K is not convex. In certain cases, solutions obtained are not unique. Moreover, counter examples are also presented for the authenticity of the main results.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.144-149
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• 2011

A study to determine the optimal jet conditions for maximizing altitude of the sounding rocket is conducted. The behavior of a simplified linear momentum equation including aerodynamic drag is investigated. The analytic solutions are obtained and compared with numerical solutions. It is shown that there are the optimal jet conditions for maximizing altitude of a sounding rocket according to the rocket mass ratio.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.38.6-38
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• 2001

This paper presents a steady state optimal control algorithm for the weakly coupled discrete time bilinearsystems. The optimal solution for the overall system is obtained by solving a sequence of reduced order algebraic Riccati equations with an arbitrary accuracy. The obtained solutions converge to the optimal solutions by using the iteration method. We verify the proposed method by applying it to a real world numerical example.

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.771-794
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• 2012

This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

• Journal of Astronomy and Space Sciences
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• v.25 no.3
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• pp.255-266
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• 2008

The current paper presents application of a new analytic solution in general relative motion to spacecraft formation flying in an elliptic orbit. The calculus of variations is used to analytically find optimal trajectories and controls for the given problem. The inverse of the fundamental matrix associated with the dynamic equations is not required for the solution in the current study. It is verified that the optimal thrust vector is a function of the fundamental matrix of the given state equations. The cost function and the state vector during the reconfiguration can be analytically obtained as well. The results predict the form of optimal solutions in advance without having to solve the problem. Numerical simulation shows the brevity and the accuracy of the general analytic solutions developed in the current paper.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1249-1262
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• 2010

An approximate alternating linearization decomposition method, for minimizing the sum of two convex functions with some separable structures, is presented in this paper. It can be viewed as an extension of the method with exact solutions proposed by Kiwiel, Rosa and Ruszczynski(1999). In this paper we use inexact optimal solutions instead of the exact ones that are not easily computed to construct the linear models and get the inexact solutions of both subproblems, and also we prove that the inexact optimal solution tends to proximal point, i.e., the inexact optimal solution tends to optimal solution.