• 한국환경과학회지
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• 제5권2호
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• pp.229-241
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• 1996

This study was performed to find the most desirable emission reduction for each mobile source pollutant and the optimal control strategy at a given level of expenditures in Pusan City in 2000 by using the interactive s-constraint method developed by Chang-Hyo Lee and Hyung-Wook Kim, which isone of the mathematical programming models. The most desirable emission reduction is 7093 ton/year for particulate (TSP), 4871 ton/year for NOx, 5148 ton/year for HC and 36779 ton/year for CO. The optimal control strategy is as follows; 1. As to passenger car and taxi, limiting VKT (vehicle kilometers travelled) in congested areas will be necessary. In addition to this, improving vehicie inspection Program should be enforced. 2. As to small-gasoline bus, traffic adaptive control system will be necessary. 3. As to small-diesel bus, non-adjustable engine parameters will have to be applied. .4. As to heal bus and heart truck, catalytic trap oxidizer and limiting VKT in congested areas will do necessary. 5. As to motorcycle, 2-cycle motorcycles should be converted to 4-cycle motorcycles.

• Journal of applied mathematics & informatics
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• 제30권5_6호
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• pp.759-772
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• 2012

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1992년도 가을 학술발표회 논문집
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• pp.7-19
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• 1992

An efficient approach to limit analysis is presented whereby a continuous perfectly plastic structure is replaced by a discrete mathematical model. It is formulated as a mathematical programming problem using the static theorem of plasticity. The discretization is accomplished by writing the governing equilibrium equations in finite difference form, and is combined with piecewise linearization of the nonlinear yield curve, thus converting the formulation into a linear programming exercise. Examples of reported cases involving plates and shells are solved to illustrate the ease of application of the present method, its flexibility and accuracy - features which it make attractive to practising engineers.

• 한국산업정보학회논문지
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• 제1권1호
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• pp.29-62
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• 1996

In this paper, the problem of determining cyclic schedules for a material handling hoist in the printed-circuit-board(PCB) electroplating line is considered. The objective of this research is to determine an optimal simple-cycle schedule of the hoist which in turn maximizes the line throughput rate. Previous approaches to the cyclic hoist scheduling problem are all mathematical programming-based approaches to develop cyclic schedules(Mixed Integer Programming, Linear Programming based Branch and Bound, Branch and Bound Search Method and so on). In this paper, a genetic algorithm-based approach for a single hoist scheduling in the PCB electroplating line is described. Through some experiments for the well known example data and randomly generated data, the proposed algorithm is shown to be more efficient than the previous mathematical programming-based algorithm.

• Journal of applied mathematics & informatics
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• 제24권1_2호
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• pp.449-460
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• 2007

Several fuzzy approaches can be considered for solving multi-objective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

• Structural Engineering and Mechanics
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• 제62권3호
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• pp.303-310
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• 2017

The model updating problems, which are to find the optimal approximation to the discrete quadratic model obtained by the finite element method, are critically important to the vibration analysis. In this paper, the structured model updating problem is considered, where the coefficient matrices are required to be symmetric and positive semidefinite, represent the interconnectivity of elements in the physical configuration and minimize the dynamics equations, and furthermore, due to the physical feasibility, the physical parameters should be positive. To the best of our knowledge, the model updating problem involving all these constraints has not been proposed in the existed literature. In this paper, based on the semidefinite programming technique, we design a general-purpose numerical algorithm for solving the structured model updating problems with incomplete measured data and present some numerical results to demonstrate the effectiveness of our method.

• 산업경영시스템학회지
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• 제19권38호
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• pp.139-146
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• 1996

In this thesis, we suggest the application of dock scheduling which is based on zero-one integer programming. A knowledge based system for dock scheduling was developed to implement this mathematical method.

• Structural Engineering and Mechanics
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• 제76권6호
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• pp.799-821
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• 2020

The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

• 한국경영과학회지
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• 제6권1호
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• pp.15-23
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• 1981

This paper deals with cross impact analysis for technology assessment. The focus of the paper is to develop new technique of cross impact matrix using goal programming method. In this study, the idea of cross impact analysis based on scenario generation method especially SMIC-74 (2) is expanded. Critical literature review on SMIC-74 is presented to discuss the mathematical rationale of consistent probability in cross impact analysis. A new model of cross impact analysis using goal programming to overcome the shortcomings of the scenario generation technique especially SMIC-74 is developed. This new technique is also applied to the assessment of the air pollution problems in Seoul Metropolitan area in Korea. The results of analysis give us following findings 1) Cross impact analysis using goal programming produce more meaningful solutions comparing to those of SMIC-74 2) Theoretical rationale of the objective function in the newly developed technique is more appropriate than that of SMIC-74.

• 한국시뮬레이션학회논문지
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• 제5권2호
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• pp.85-93
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• 1996

Simulation is commonly used to find the best values of decision variables for problems which defy analytical solutions. This objective is similar to that of optimization problems and thus, mathematical programming techniques may be applied to simulation. However, the application of mathematical programming techniques, e.g., the gradient methods, to simulation is compounded by the random nature of simulation responses and by the complexity of the statistical issues involved. In this paper, therefore, we explain the Reverse-Simulation method to optimize a simulation model in a single simulation run. First, we point the problem of the previous Reverse-Simulation method. Secondly, we propose the new algorithm to solve the previous method and show the efficiency of the proposed algorithm.