• Nuclear Engineering and Technology
• /
• 제40권5호
• /
• pp.327-348
• /
• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• 재무관리연구
• /
• 제2권1호
• /
• pp.21-34
• /
• 1986

The purpose of this study is to analyse the risk and uncertainty involved in the capital budgeting which is executed in long periods and requires massive capital expenditure. Under risk and uncertainty conditions, the estimates in the capital budgeting are random variables rather than known constants. Two approaches have emerged in performing economic analysis that explicitly incorporate risk and uncertainty conditions in the analysis. One approach is to develop a descriptive model which describes the economic performance of an individual investment alternative. But no recomendation would be forthcoming from the model. Rather, the decision-maker would be furnished descriptive information concerning each alternative; the final choice among the alternatives would required a separate action. The second approach is to develop a normative model which includes an objective function to be maximized or minimized. The output from the model prescribes the course of action to be taken. Owing to the fact that the normative approach considers the fitness of criteria for decision-making its reasonableness looks better. But it is almost imposible that we correctly and easily derive the individuals' utility function. So within we recognize the limits of the descriptive methods, it is more practicle to analyse the investment alternatives by sensitivity analysis.

• 산업경영시스템학회지
• /
• 제22권51호
• /
• pp.151-161
• /
• 1999

For many decades, Deterministic DCF approach has been widely used to evaluate investment opportunities. Under new manufacturing conditions involving uncertainty and risk, the DCF approach is not appropriate. In DCF, Risk is incorporated in two ways: certainty equivalent method, risk adjusted discount rate. This paper proposes a determination method of the Risk Adjusted Discount Rate for economically decision making advanced manufacturing technologies. Conventional DCF techniques typically use discount rate which do not consider the difference in risk of differential investment options and periods. Due to their relative efficiency, advanced manufacturing technologies have different degree of risk. The risk differential of investments is included using $\beta$ coefficient of capital asset pricing model. The comparison between existing and proposed method investigated. The DCF model using proposed risk adjusted discount rate enable more reasonable evaluation of advanced manufacturing technologies.

• 산업공학
• /
• 제6권2호
• /
• pp.151-169
• /
• 1993

In this research, we proposed "coefficient of inequality" as a measure of distributional inequality for an alternative, which is defined as the area between the diagonal line from 0 to 1 and the Lorenz curve of the given alternative. Next, we showed theoretical relationship between stochastic dominance and the coefficient of inequality as a means to determine the preferred alternative when decision is made with incomplete information about decision maker's utility function. Then, two experiments were performed to test subject‘s attitude toward risk. The results of the experiments support the idea that when a decision maker is risk averse or risk prone, he/she can use the coefficient of inequality as a decision rule to choose the preferred alternative instead of using stochastic dominance. Thus, according to decision maker’s attitude toward risk, the decision rule proposed here can be used as a valuable aid in decision making under uncertainty with incomplete information.

• 산업경영시스템학회지
• /
• 제6권9호
• /
• pp.111-124
• /
• 1983

The basic model of decision problem the enterprise is conforonted with includes the following 3 elements ; 1) Elements that can not be controlled by the decision maker : In the thesis elements are named environmental variables, and varied itself according to the change of environmental condition. 2) Elements that can be controlled by the decision maker ; These elements are called decision elements in the thesis and variable according to the event. 3) object of decision making : The degree of achievement to the object is identified by taking various criteria- The index indicating the degree of achievement to the object whatever criterion is applied is called object function in the thesis. It's the fanetion of environmental variable, decision variable and object function. The relation between them brings forth the relation formula that characterize the each problem. The basic types of decision making model use in the thesis are as following ; 1) The problem of decision making under conditions of certainty. 2) The problem of decision making under conditions of risk. 3) The problem of decision making under conditions of uncertainty. 4) The problem of decision making under competitive condition. in general case that the Profit of two decision makers varies, what we regard the decision that make the sum of profit of two men maximum as the best choice for two men has a reasonability in certain case. When the sum of profit two men is zero, by taking toe promise that ail of them art according to the min-max criteria and by extending the object of choice to the mixed strategy. We certify the existance of equilibrium solution and admit them as the best solution of competitive model in general.

• 산업경영시스템학회지
• /
• 제22권52호
• /
• pp.311-322
• /
• 1999

Major problems involved in an electrical utility expansion planning within a time horizon are how to efficiently deal with objectives considering multiple factors and uncertainty. But justification factors in study these days have considered only quantitative factors except qualitative factors. Therefore, the purpose of this paper is to develop a new model for economic evaluation of nuclear power plants through the scoring model with the quantitative and qualitative factors under uncertainty. The quantitative factors use a levelized generation cost method considering time value of money. Especially, the environmental, risk, and safety factors in this paper have been also explained for the rational economic justification of the qualitative factors under uncertainty. This paper not only proposes a new approach method using the scoring model in evaluating economy of the nuclear power plant in the long term, but also provides the more efficient decision making criterion for nuclear power plants under uncertainty.

• Nuclear Engineering and Technology
• /
• 제35권1호
• /
• pp.64-79
• /
• 2003

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems.

• 한국경영과학회지
• /
• 제20권2호
• /
• pp.39-60
• /
• 1995

In this paper, an integration of stochastic dynamic programming (SDP), integer goal programming (IGP) and analytic hierarchy process (AHP) is proposed to handle multiobjective-multicriteria sequential decision making problems under uncertainty inherent in R & D investment planning. SDP has its capability to handle problems which are sequential and stochastic. In the SDP model, the probabilities of the funding levels in any time period are generated using a subjective model which employs functional relationships among interrelated parameters, scenarios of future budget availability and subjective inputs elicited from a group of decision makers. The SDP model primarily yields an optimal investment planning policy considering the possibility that actual funding received may be less than anticipated one and thus the projects being selected under the anticipated budget would be interrupted. IGP is used to handle the multiobjective issues such as tradoff between economic benefit and technology accumulation level. Other managerial concerns related to the determination of the optimal project portifolio within each stage of the SDP model. including project selection, project scheduling and annual budget allocation are also determined by the IGP. AHP is proposed for generating scenario-based transformation probabilities under budgetary uncertainty and for quantifying the environmental risk to be considered.

• 한국기후변화학회지
• /
• 제4권1호
• /
• pp.11-26
• /
• 2013

본 연구는 기후변화 불확실성 하의 용수공급계획을 위해 로버스트 의사결정(Robust Decision Making, RDM) 기법을 국내의 유역에 시범 적용하고, 가중치와 평가기준 점수를 합산하는 일반적인 형태의 표준 의사결정(Standard Decision Making, SDM) 결과와 비교하였다. RDM은 기후변화 시나리오의 발생 유무에 관한 확률 정보에 의존하지 않고 어떤 시나리오 하에서도 위험 수준 이하의 변동이 발생하지 않는 대안을 유도할 수 있는 후회기준(Regret criterion)을 사용하여 대안의 순위를 결정한다. SDM과 RDM에 의해 산정된 순위를 비교하기 위하여 안동댐과 임하댐 유역에 용수공급계획 사례를 작성하여 각 기법을 적용하였다. 다양한 기후변화 시나리오를 작성하고, 댐 수위를 조정한 6개의 대안을 가상적으로 구축한 후, SDM 및 RDM 기법으로 대안의 순위를 산정하였다. 그 결과, SDM과 RDM 사이에는 동일한 시나리오와 대안을 사용했음에도 불구하고, 평균적으로 0.33~1.33순위 차를 나타내었다. 본 연구는 수자원 분야에서 기후변화 적응에 대한 연구가 미비한 가운데 기후변화 불확실성을 고려하여 적절한 의사결정 기법 연구를 시도하였다는 것에 그 의의가 있으며, 향후 다양한 상황 하에 RDM의 효과를 보다 면밀히 분석해야 할 것으로 사료된다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2020년도 학술발표회
• /
• pp.171-171
• /
• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.