• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.20-33
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• 2002

This paper deals with assigning defensive counter air aircraft to the moving target in the air. Recently various kinds of allocation problems have been researched for fixed targets using offensive aircrafts. However, the counter air allocation problems for attacking aircrafts with considering the time and the threat have not been studied much. The main objective of this study is to mininize the time to intercept and the threat values simultaneously by using goal programming. The optimal solution by using an integer goal programming and a branch and bound algorithm is found and analyzed. By applying this model to real situation, we expect to reduce the time and number of sorties for destroying enemy aircraft, respectively.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.100-114
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• 2000

This paper demonstrates the application of a Quality Function Deployment (QFD) and Zero-One Goal Programming model for selecting interdependent information system project selection, there are a few research for interdependent IS project selection. Effective project evaluation necessities incorporating the many conflicting objectives of decision maker(s) into decision models. Among the many proposed methodologies of multi-criteria decision making (MCDM), Goal Programming (GP) is the most popular and widely used. The model departs from an earlier GP formulation of the problem that suggested QFD method for selection of priorities among the considered attributes or criteria. The application of the proposed methodology illustrated through an example.

• Korean Management Science Review
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• v.28 no.1
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• pp.141-158
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• 2011

This study concerns with an applicability of the management science approach to the score adjustment among the College Scholastic Aptitude Test(CSAT) optional subjects. A linear programming model is developed to minimize the sum of score distortions between optional subjects. Based on the analysis of the 377,089 CSAT(2010) applicants' performances in social science test section, this study proposes a new approach for the score equating or linking method of the educational measurement theory. This study makes up for the weak points in the previous linear programming model. First, the model utilize the standard score which we can get. Second, the model includes a goal programming concept which minimizes the gap between the adjusting goal and the result of the adjustment. Third, the objective function of the linear programing is the weighted sum of the score distortion and the number of applicants. Fourth, the model is applied to the score adjustment problem for the whole 11 optional subjects of the social science test section. The suggested linear programming model is a generalization of the multi-tests linking problem. So, the approach is consistent with the measurement theory for the two tests and can be applied to the optional three or more tests which do not have a common anchor test or a common anchor group. The college admission decision with CSAT score can be improved by using the suggested linear programming model.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.512-516
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• 1998

Fuzzy mathematical programming (FMP) can be treated an uncertainty condition using fuzzy concept. Further, it can be extended to the multiple objective (or goal) programming problem, naturally. But we feel that FMP have some shortcomings such as the fuzzy number in FMP is the one dimesional possibility set, so it can not be represented the relationship between them, and, in spite of FMP includes some (uncertainty) fuzzy paramenters, many alogrithms are only obtained a crisp solution.In this study, we propose a method of FMS. Our method use the scenario approach (or fuzzy random variables) to represent the relationship between fuzzy numbers, and can obtain the fuzzy solution.

• Journal of Biosystems Engineering
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• v.8 no.2
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• pp.69-85
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• 1983

Nonlinear Goal Programming(NGP)이 Multiple Objective Decision Making(MODM) 문제(問題)를 적정화(適正化)할 수 있는 방법(方法)으로 소개(紹介)가 되었다. 그리고 6 가지의 벼 조제(調製) 및 저장시설(貯藏施設)을 분석(分析)한 후, NGP에 의(依)하여 적정시설설계(適正施設設計)를 하기 위하여 Model Systems를 개발(開發)하고 그에 의(依)하여 MODM의 수학적(數學的) 모형(模型)을 개발(開發)하였다.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.2
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• pp.45-50
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• 1984

This paper is concerned with the facility location-allocation problem (FLAP) with multiple objectives. A branch-and-bound procedure is presented to solve the mixed zero-one integer goal programming problem which is to determine facility locations from given candidate locations and to allocate facility capacity to given customer markets simultaneously. A numercial example is given to illustrate this procedure.

• IE interfaces
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• v.1 no.1
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• pp.17-26
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• 1988

This paper describes a nonlinear goal programming approach to the optimal composition of composite solid propellant taking multiple characteristics into consideration synchronously. The nonlinear goal programming model with response functions, restrictions and the optimal value of each characteristic is developed using Scheffe's "Experiments with mixtures" and preference weighting system. Objective functions are described based on process, performance and assurance characteristics. The systematic approach to optimal composition in this study is proved efficient through a CTPB-AL-AP propellant which is one of composite solid propellant systems.

• Journal of Biosystems Engineering
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• v.9 no.1
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• pp.46-52
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• 1984

MODM(Multiple Objective Decision Making) 문제(問題)로서의 벼 건조(乾燥) 및 저장시설(貯藏施設)의 설계문제(設計問題)에 NGP(Nonlinear Goal Programming)를 이용(利用)하여 어떻게 적정화(適正化)할 수 있는가를 예제(例題)를 통하여 제시(提示)한 후, $1,762m^2$의 수확량(收穫量)에 대한 6가지의 벼 건조(乾燥) 및 저장시설(貯藏施設)에 대한 각각의 적정(適正)시스템을 제시(提示)하였다.