• Title/Summary/Keyword: Decision under risk

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Decisions under risk and uncertainty through the use of Choquet integral

  • Narukawa, Yasuo;Murofushi, Toshiaki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.555-558
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    • 2003
  • The Choquet-Stieltjes integral is defined. It is shown that the Choquet -Stieltjes integral is rep-resented by a Choquet integral. As an application of the theorem above, it is shown that Choquet expected utility model for decision under uncertainty and rank dependent utility model for decision under .risk are respectively same as their simplified version.

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Identification of Prevailing Risk Attitudes in Various Risk Situations (다양한 위험상황에서의 지배적 위험태도의 파악)

  • Kang, Tae-Geon;Cho, Sung-Ku
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.4
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    • pp.437-447
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    • 1999
  • Previous researches on risk attitudes or on the typical utility functions have mostly focused on how the risk attitude of decision maker varies when changes are made in one or two lottery reference points such as consequence domain and magnitude of probability under assumed risk situations represented by simple lotteries. It is, however, very difficult to forecast dominant risk attitudes under risk situations which exhibit a complex combination of many reference points. In this study, twelve risk situations which a decision maker may confront in real decision-making situations were formulated by combining in various ways three reference points, that is, magnitude of probability, consequence domain, and magnitude of gain or loss. Then through a questionnaire dominant risk attitudes under every assumed risk situation were investigated, and the general shape of utility function implied by the experimental results were derived. Results of the present study show that none of the three reference points have dominant effect over the others due to complicated interaction between them, and given the twelve risk situations the observed risk attitude widely varies from strong risk taking to strong risk aversion.

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A Study on the Investment Decision of Offshore Aquaculture under Risk (위험 하에서의 외해가두리양식업 투자의사결정에 관한 연구)

  • Kim, Do-Hoon;Choi, Jong-Yeol;Lee, Jung-Uie
    • The Journal of Fisheries Business Administration
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    • v.39 no.2
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    • pp.109-123
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    • 2008
  • This study is aimed to establish an investment decision model for offshore aquaculture project of rock bream in Korea using a certainty equivalent method (CEM) based on the expected utility theory and to investigate its economic viability under risk and uncertainty. In the analysis with CEM, the effects of risk attitude and risk level on investment and risk premium were examined and the impacts of various risk and uncertainty factors on the investment decision were also assessed. In addition, the outcomes were compared to those evaluated by the traditional net present value (NPV) method. Results show that risk premium grew as the investors became more risk averse and uncertainty level (the variance of NPV) increased. Consequently, the certainty equivalent value was predicted to decrease from the value assessed by the traditional NPV method.

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Stochastic Dominance and Distributional Inequality (추계적 우세법칙과 분포의 비상등성)

  • Lee, Dae-Joo
    • IE interfaces
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    • v.6 no.2
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    • pp.151-169
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    • 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.

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Navigation safety domain and collision risk index for decision support of collision avoidance of USVs

  • Zhou, Jian;Ding, Feng;Yang, Jiaxuan;Pei, Zhengqiang;Wang, Chenxu;Zhang, Anmin
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.340-350
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    • 2021
  • This paper proposes a decision support model for USVs to improve the accuracy of collision avoidance decision-making. It is formed by Navigation Safety Domain (NSD) and domain-based Collision Risk Index (CRI), capable of determining the collision stage and risk between multiple ships. The NSD is composed of a warning domain and a forbidden domain, which is constructed under the constraints of COLREGs (International Regulations for Preventing Collisions at Sea). The proposed domain based CRI takes the radius of NSD in various encounter situations as threshold parameters. It is found that the value of collision risk in any directions can be calculated, including actual value and risk threshold. A catamaran USV and 6 given vessels are taken as study objects to validate the proposed model. It is found that the judgment of collision stage is accurate and the azimuth range of risk exists can be detected, hence the ships can take direct and effective collision avoidance measures. According to the relation between the actual value of CRI and risk threshold, the decision support rules are summarized, and the specific terms of COLREGs to be followed in each encounter situation are given.

Diagnostic Classification Scheme in Iranian Breast Cancer Patients using a Decision Tree

  • Malehi, Amal Saki
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.14
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    • pp.5593-5596
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    • 2014
  • Background: The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. Materials and Methods: The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Results: Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Conclusions: Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

A Determination Method of the Risk Adjusted Discount Rate for Economically Decision Making on Advanced Manufacturing Technologies Investment (첨단제조기술 투자의 경제적 의사결정을 위한 위험조정할인율의 결정방법)

  • 오병완;최진영
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.51
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    • pp.151-161
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    • 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.

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Multiobjective Decision Model with Consideration of Flexibility in Sequential Capital Budgeting

  • Min, Kye-Ryo;Park, Kyung-Soo
    • Journal of the military operations research society of Korea
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    • v.7 no.1
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    • pp.53-80
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    • 1981
  • This paper explores a rational investment decision model in sequential capital allocation process under capital rationing. A method is proposed for measuring the new investment decision factor which is the flexibility that describes the future availability of invested funds. This flexibility is important in sequential decision process. Also presented is a multiobjective (MO) decision model into which flexibility is incorporated with the profit and risk factors. The effectiveness of this criterion is compared with the expected present value and the mean-semivariance criteria through a simulation model.

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A Multi-Phase Decision Making Model for Supplier Selection Under Supply Risks (공급 리스크를 고려한 공급자 선정의 다단계 의사결정 모형)

  • Yoo, Jun-Su;Park, Yang-Byung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.112-119
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    • 2017
  • Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.