Earticle

The total yield of Pinus koraiensis stands was reviewed along forest function by using goal programming, which is one of the operations research techniques. The 4 kinds of management goals are set to identify timber production in the Research Forest of Kangwon National University. As a result, scenario 1 was estimated the best timber production over 2,073 ha area and also 588 ha in the third quarter was showed the most timber harvest. The rate of timber harvest was separated by 10 to 50 percent in non-timber forest function in the scenario 1 and that model was applied to the Research Forest of Kangwon National University. The structure of the area and volume is showed to be balanced quarterly when rate of timber harvest at 10 to 20 percent.

Analytic Network Process (ANP) has been widely used in solving many complicated decision making problems. An approach to acquire the comprehensive weights of interval-valued Analytic Network Process (IV-ANP) is proposed. Firstly, the independent local interval-valued weights are obtained by solving the goal programming for interval-valued pairwise comparison matrices. Based on the interaction and feedback relationships among criteria and/or indices, an unweighted interval-valued supermatrix is formed. To avoid loss of information, an extreme value method is developed for acquiring the global weights of IV-ANP. Secondly, the alternatives are ranked on the basis of interval-valued preference order. Finally, with the interaction and feedback relationships between criteria and/or indices being considered, an index system for assessing the risk of dynamic alliance is presented. With the uncertain and inaccurate information during the evaluation process being considered, the proposed IV-ANP method is applied for risk assessment of dynamic alliance, and sensitivity analyses for some key risk factors are performed to show their impacts on the risk levels of alliance enterprises.

To select the best Third-Party Logistics(TPL) transportation suppliers(companies) it is essential to make a trade off between quantitative and qualitative factors. When many constraints exist, choosing the companies becomes more complicated. In this paper an integration of an analytical hierarchy process and multicriteria goal programming is proposed to consider both quantitative and qualitative factors in choosing the best transportation companies within constrained environment. First, through the previous studies, we derive important factors and priorities by applying Analytic Hierarchy Process(AHP). Then, along with the results obtained by AHP, to choose the best transportation companies we establish multicriteria Goal Programming(GP) model considering fixed, total and transportation cost,rate of damaged goods and rate of delayed goods as major criteria. We also derive optimal quantities of goods transported from each selected transportation company to destinations based upon the proposed method.

홍수기 다목적댐 운영의 목적은 홍수조절용량을 최대한 이용하여 하류 주요 지점의 첨두홍수량을 저감시키거나, 계획홍수량을 초과하지 않도록 방류량과 방류시점을 조절함으로써 홍수 피해규모를 최소화하는 것이다. 본 연구에서는 홍수기 다목적댐 운영에서 다목적 최적화의 한 형태인 goal programming의 적용성을 검토하였다. 실제 강우사상을 이용하여 단일저수지 운영과 저수지 연계운영을 실시하였다. 단일 저수지 운영을 적용하기 위한 시험유역으로는 충주댐 유역을 선정하였고 저수지 연계운영을 적용하기 위한 시험유역으로는 안동댐과 임하댐 유역을 선정하였다. goal programming의 결과 분석을 위해 저수지 모의운영 모형인 HEC-5 모형의 결과와 비교, 분석하였다. goal programming을 이용할 경우 HEC-5 운영결과보다 안정적인 운영결과를 얻을 수 있었다. goal programming을 이용한 최적화 운영의 경우 전구간의 유입량을 알고 있다는 점에서 실제 저수지 운영과는 차이가 있다. 그러나 적절한 제약조건을 적용하고 홍수예경보를 이용하여 예보된 유입량을 활용하면 최적의 방류시점과 방류량을 산정하여 홍수기 다목적댐을 효율적으로 운영할 수 있으며 주요 지점의 홍수량도 저감할 수 있을 것으로 판단된다.

In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the outgoing quality and the average total inspection cost A fuzzy goal programming model and its solution procedure are proposed for the managers whose management objectives on the two evaluation criteria are not rigorous. To study the sensitivity of quality characteristic dependence on the resulting inspection plans, a numerical example is solved several times for a dependent model.

An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system nay be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.

홍수기 다목적댐 운영의 목적은 홍수조절용량을 최대한 이용하여 하류 주요 지점의 첨두홍수량을 저감시키거나, 계획홍수량을 초과하지 않도록 방류량과 방류시점을 조절함으로써 홍수피해규모를 최소화하는 것이다. 따라서 홍수기 다목적댐 운영에 있어 가장 중요한 것은 최적의 방류시점과 방류량의 결정이며 이를 통해 홍수기말 이수용량을 최대로 확보 하는 점이다. 본 연구에서는 다목적 최적화기법의 하나인 goal programming을 이용하여 홍수기 저수지 최적운영을 실시하였다. goal programming은 선형계획법 또는 비선형계획법을 이용하여 두 개 이상의 목적을 가진 문제의 최적 대안을 구하기 위해, 목표값으로부터의 편차의 합을 최소화하여 최적화하는 기법이다. 홍수기 다목적댐 운영에서 goal programming의 적용성을 검토하기 위해 실제 홍수 사상을 이용하여, 단일저수지 운영과 저수지 연계운영을 실시하였다. 단일저수지 운영을 적용하기 위한 시험유역으로는 충주댐 유역을 선정하였고 저수지 연계운영을 적용하기 위한 시험유역으로는 안동댐과 임하댐 유역을 선정하였다. goal programming의 결과 분석을 위해 저수지 모의운영 모형인 HEC-5 모형의 결과와 비교, 분석하였다. 검토 결과 goal programming을 이용할 경우 홍수기 말에 저수지 수위를 홍수기제한수위로 유지할 수 있었으며 주요 지점의 홍수량을 매 시간 적절히 계획홍수량 아래로 유지할 수 있었다. goal programming을 이용한 최적 운영의 경우 전 구간의 유입량을 알고 있다고 가정한 점에서 실제 저수지 운영과는 차이가 있으나, 적절한 제약조건을 적용하고 홍수예경보를 이용하여 예보된 유입량을 활용하면 최적의 방류량 시점과 방류량을 산정하여 홍수기 다목적댐을 효율적으로 운영할 수 있으며 주요 지점의 홍수량도 저감할 수 있을 것으로 판단된다.

The purpose of multipurpose reservoir operation in flood season is to reduce the peak flood at a control point by utilizing flood control storage or to minimize flood damage by controlling release and release time. Therefore, the most important thing in reservoir operation for flood season is to determine the optimal release and release time. In this study, goal programming is used for the optimal reservoir operation in flood season. The goal programming minimizes a sum of deviation from the target value using linear programming or nonlinear programming to obtain the optimal alternative for the problem with more than two objectives. To analyze the applicability of goal programming, the historical storm data are utilized. The goal programming is applied to the reservoir system operation as well as single reservoir operation. Chungju reservoir is selected for single reservoir operation and Andong and Imha reservoirs are selected for reservoir system operation. The result of goal programming is compared with that of HEC-5. As a result, it was found that goal programming could maintain the reservoir level within flood control level at the end of a flood season and also maintain flood discharge within a design flood at a control point for each time step. The goal programming operation is different from the real operation in the sense that all inflows are assumed to be given in advance. However, flood at a control point can be reduced by calculating the optimal release and optimal release time using suitable constraints and flood forecasting system.

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.

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.

본 연구에서는 Fuzzy Goal Programming을 이용하여 배전계통에서 분산형 전원의 설치 및 운영에 대한 새로운 방안을 제시하였다. 분산형전원의 설치 및 운영을 위하여 최적화 알고리즘의 탐색공간의 크기를 줄이면서 계통상황 변동에 적합하게 정식화하였다. 특히, 목적함수인 계통 유효전력손실과 제약조건인 분산형전원의 수 또는 총용량 및 모선전압에 대하여 각각의 부정확한 성질을 평가하기 위하여 퍼지 Goal Programing으로 모델링 하였으며, 유전알고리즘을 사용하여 최적해를 탐색하였다.

This paper presents the method for the placement and operation of dispersed generator systems(DGs) using fuzzy goal programming in distribution systems. For the placement and operation of DGs the problem is formulated with reduction of search spaces and flexibility of system situations. Especially, the original objective function and constraints are transformed by fuzzy goal programming to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm.

In this paper, we propose a multi-Criteria decision making approach to address the problem of finding the best possible solution in credit unions. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses the Euclidean distance method to measure distances of all possible solutions from the identified ideal solution. The possible optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the Problem.

This paper with the development and analysis of a quantitative model for reducing operating budgets of the academic units of small private university, while reflecting the diverse goals of the university. A zero-one goal programming approach is used to design and implement the model for budgetary decision making. The goal programming model can facilitate academic planning and decision-making by providing valuable information.

Supply chain management is integrated efforts and activities for a supply chain and supply chain design can be a critical factor in improving the performance of a supply chain. Logistics network decisions are an essential part of supply chain design. Many traditional optimization models for logistics network decisions are based mainly on cost minimization. However, today’s global competitiveness requires a more realistic logistics network decisions which employ integrated performance measures e.g. cost, quality, service etc. The objective of this research is to develop an optimization model for logistics network decisions considering not only cost but also service factors as performance measure, where the service factors are reliability of delivery time, reliability of physical condition of products, flexibility of normal/urgent deliveries. The contribution of this research is that we consider the service factors and use goal programming approach for the conflicting goals plus analytical hierarchical process for estimating weights. A non-linear, non preemptive, goal programming formulation is proposed with numerical examples.

This paper presents a fuzzy-goal programming(FGP) approach for Bi-Level Linear Multiple Objective Decision Making(BLL-MODM) problem in a large hierarchical decision making and planning organization. The proposed approach combines the attractive features of both fuzzy set theory and goal programming(GP) for MODM problem. The GP problem has been developed by fixing the weights and aspiration levels for generating pareto-optimal(satisfactory) solution at each level for BLL-MODM problem. The higher level decision maker(HLDM) provides the preferred values of decision vector under his control and bounds of his objective function to direct the lower level decision maker(LLDM) to search for his solution in the right direction. Illustrative numerical example is provided to demonstrate the proposed approach.

Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design as interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputer for solving goal programming problems.

We propose a simple new analytic method for solving a fuzzy goal programming (FGP) problem with general membership functions of fuzzy goals and re-examine a previously defined method for dealing with fuzzy weights for each of the goals. Several illustrative examples are given.

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

This paper presents a goal-programming (GP) model for management decision-making for sugarcane fertilizer mix problems. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses Euclidean distance function to measure distances of all possible solutions from the ideal solution. The optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the problem. The optimum solution corresponds to the appropriate priority structure of the problem in the decision-making context. furthermore, the results obtained from sensitivity analysis on the cost of combination of fertilizers confirm the priority structure.