• Management Science and Financial Engineering
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• v.21 no.2
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• pp.9-11
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• 2015

This note is concerned with the use of incomplete weights in multiple criteria decision making. In an earlier study, an optimistic use of incomplete weights is developed to prioritize decision alternatives, which applies the most favorable set of weights to the alternative to be evaluated. In this note, we develop a method for a pessimistic use, thereby applying the least favorable weight set to the evaluated alternative. This development makes possible a more detailed prioritization of competing alternatives, and hence enhances decision-making powers.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.1-27
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• 2007

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.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.249-273
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• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Research in Community and Public Health Nursing
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• v.27 no.1
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• pp.43-50
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• 2016

Purpose: The purpose of this study was to investigate the relationship of depression and smartphone dependency with female college students' career decision-making self efficacy. Methods: This was a descriptive study. The survey participants were 497 female college students in M City and S City. Data were collected from November 16 to December 4, 2015 using self-report questionnaires including BDI (Beck Depression Inventory), Smartphone Dependency Scale, and CDMSES-SF (Career Decision-Making Self Efficacy Scale-Short Form). Data were analyzed through descriptive statistics, independent-samples t-test, ANOVA, and stepwise multiple regression. Results: Career decision-making self efficacy showed significant differences according to religion. Smartphone dependency was found to have a statistically significant negative correlation with career decision-making self efficacy and a positive correlation with depression. Depression was found to have a statistically significant negative correlation with career decision-making self efficacy. Stepwise multiple regression analysis revealed that the predictors of career decision-making self efficacy were depression (7.1%), religion (1.8%), and smartphone dependency (1.3%), accounting for a total of 10.6% of the variance. Conclusion: This study suggests that interventions to promote female college students' career decision-making self efficacy should consider their depression, religion, and smartphone dependency.

• Korean Journal of Occupational Health Nursing
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• v.22 no.4
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• pp.285-294
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• 2013

Purpose: This study aimed to explore professional autonomy, nursing work environment, and clinical decision making ability and to determine predictors of clinical decision making ability among clinical nurses. Methods: A cross-sectional design was used in this study and 263 clinical nurses were selected from advanced-level hospitals with over 500 beds located in D metropolitan city. Independent t-test, ANOVA, Pearson's correlation coefficients and hierarchical multiple regression analyses were done with the SPSS/WIN 20.0 program. Results: Clinical nurses reported moderate levels of professional autonomy, nursing work environment and clinical decision making ability. Marital status, professional autonomy and nursing work environment accounted for 25% of variance in clinical decision making ability required in various clinical settings. Importantly, being married, higher level of professional autonomy, and greater satisfaction with work environment were significantly associated with better decision making ability. Conclusion: Findings indicate that improving the quality of decision making in the healthcare settings requires awareness of the multiple effects of individual, occupational and environmental features. Nurses' ability to make effective clinical decisions may rely on personal characteristics, the degree of autonomy in their job, and nurses' satisfaction with their work environment.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.59-64
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• 2005

MDMG(Multiple Decision-Making Group) problems comprise those of UDMG(Unit Decision-Making Group) which contradict each other. For the evaluation problem of port competitiveness, it has the complicated evaluation characteristics of multi-strata-complex and multi-attributes. Especially, it becomes typical MDMG problems in the evaluation which a great number of decision makers such as shipping companies, freight forwarders, logistics companies and researchers participate in This evaluation of complex problems needs the compensated process of weight which rationally unites heterogeneous preferences of each of groups. In this respect, the purpose of this study is to remove the uncertainty of the UDMG using the theory of DS (Dempster-Shafer) and present the integrated weight through the level process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.380-383
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• 2003

In this paper, we propose a fuzzy group decision making method for multiple decision maker-multiple objective programming problems to obtain the agreeable solution. In the proposed method, considering the vague nature of human subjective judgement it is assumed that each of multiple decision makers has a fuzzy goal for each of his/her own objective functions. After eliciting the membership functions from the decision makers for their fuzzy goals, total M-Pareto optimal solution concept is defined in membership spaces in order to deal with multiple decision maker-multiple objective programming problems. For generating a candidate of the agreeable solution which is total M-Pareto optimal, the extended weighted minimax problem is formulated and solved for some weighting vector which is specified by the decision makers in their subjective manner, Given the total M-Pareto optimal solution, each of the derision makers must either be satisfied with the current values of the membership functions, or update his/her weighting vector, However, in general, it seems to be very difficult to find the agreeable solution with which all of the decision makers are satisfied perfectly because of the conflicts between their membership functions. In the proposed method, each of the decision makers is requested to estimate the degree of satisfaction for the candidate of the agreeable solution. Using the estimated values or satisfaction of each of the decision makers, the core concept is desnfied, which is a set of undominated candidates. The interactive algorithm is developed to obtain the agreeable solution which satisfies core conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.87-95
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• 2008

The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

• Journal of Engineering Education Research
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• v.19 no.6
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• pp.20-31
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• 2016

The purpose of this study was to explore factors predicting career exploration behavior of engineering students. Career decision making types(rational type, intuitive type, and dependent type) and career decision making self-efficacy were included as predictors for this study. 249 engineering students in Gyeonggi-do of South Korea participated in this study and 231 data analyzed as final samples through multiple regression and mediation analysis. Results showed as follows: first, rational and intuitive decision making significantly predicted career exploration behavior. Also, career decision making self-efficacy completely mediated between these career decision making types(rational and intuitive) and career exploration behavior. The implication of the findings on practice for career education are discussed in the paper.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.25-32
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• 2023

Decision-making refers to identifying the best alternative among a set of alternatives. When a set of criteria are involved, the decision-making is called multi-criteria decision-making (MCDM). In some cases, the involved criteria may be prioritized by the human decision-maker, which determines the importance degree for each criterion; hence, the decision-making becomes prioritized multi-criteria decision-making. The essence of prioritized MCDM is raking the different alternatives concerning the criteria and selecting best one(s) from the ranked list. This paper introduces a generic multi-level algorithm for ranking multiple alternatives in prioritized MCDM problems. The proposed algorithm is implemented by a decision support system for selecting the most critical short-road requests presented to the transportation ministry in the Kingdom of Saudi Arabia. The ranking results show that the proposed ranking algorithm achieves a good balance between the importance degrees determined by the human decision maker and the score value of the alternatives concerning the different criteria.