• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.58-63
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• 2002

Recently a new multi-attribute analysis method is one of the evident areas of important points in the decision support system analysis. The area of decision support system may be broken into three primary area: idea generation, multi-attribute structured analysis method, and the integration of the results of analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system in the view of 1) brainstorming for the idea generation, 2) analytic hierarchy process as a multi-attribute structured analysis method and 3) aggregating logic model to integrate the results of individual analysis. A computer program is developed and demonstrated in internet/intranet-based decision problem. This solution builder provides decision makers a good tool for remote group decision making.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1601-1610
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• 2009

Unplanned purchase is an unexpected buying behavior affected by product or marketing stimuli. Unplanned purchase does not follow the order of the rational decision making process. Through an in-depth interview, this study classified the types of unplanned purchase of clothing and examined the decision-making processes. The results (according to the need recognition level of consumers prior to stimuli) show three types of unplanned purchase of clothing products that are classified as: the need-manifesting type, the need-embodying type, and the need-reminding type. In addition, each type is reclassified into the high-cognition type and the low-cognition type according to the cognitive effort level of consumers during the purchase decision-making process. The need-manifesting type recognized a buying need after exposure to stimuli and then engaged in unplanned purchases. The need-embodying type recognized a problem, but the purchase intention was not concrete. The need-reminding type recognized a desire to buy clothing products, but temporarily forgot it, and then later remembered the problem recognition from the past after experiencing the stimuli.

• Journal of Korean Port Research
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• v.7 no.1
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• pp.5-12
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• 1993

In complex decision making such as ill-defined system, one of the main problem is how to treat ambiguous aspect of the decision making. According to the complexity and ambiguity of the objective systems, many types of evaluation attributes are necessary for the rational decision and the relationship among the attributes become complex and fuzzy. Fuzzy integral is very effective to evalute the complex system with interaction between attributes but how to save the evaluation efforts in the decision making process of grading the membership of the objects or alternative is the problem to be tackled. Because the more object there are to evaluate, the number of decisions to made increase exponentially. Therefore, this paper aimes to propose a new evaluation algorithm based on fuzzy integral which can save the evaluator's efforts in decision making process. The proposed algorithm is constructed as follows : First, compose the fuzzy measure by introducing AHP(Analytical Hierachy Process) & mutual interaction coefficient. Second, generate fuzzy measure value of monotone family set for calculating the fuzzy integral. The effectiveness of the proposed algorithm is investigated through the example and sensitivity of interaction coefficient is illustrated.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.127-135
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• 2011

Efficient ordering of decision variables is one of the methods that find solutions quickly in the depth first search using backtracking. At this time, development of variables ordering algorithms considering dynamic and static properties of the problems is very important. However, to exploit optimal variable ordering algorithms appropriate to the problems. In this paper, we propose a problem classifying rule which provides problem type based on variables' properties, and use this rule to predict optimal type of variable ordering algorithms. We choose frequency allocation problem as a DS-type whose decision variables have dynamic and static properties, and estimate optimal variable ordering algorithm. We also show the usefulness of problem classifying rule by applying base station problem as a special case whose problem type is not generated from the presented rule.

• Journal for History of Mathematics
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• v.25 no.3
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• pp.15-27
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• 2012

This paper aims to examine Alan Turing's life at the centenary of his birth and to discuss a philosophical implication of his work by concentrating on halting theorem particularly. Turing negatively solved Hilbert's decision problem by proving impossibility of solving halting problem. In this paper I claim that the impossibility implies limits of reason, and accordingly that the marginality in cognition and/or in action should be recognized.

• Management & Information Systems Review
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• v.13
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• pp.127-140
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• 2003

Although there have been continual researches in the project scheduling problems since 1960s, the main interest has been how to improve the efficiency of a single project. The minimization problem of the project completion time given a preassigned budget might be an example. This kind of the problem is important, but estimating of the proper budget for a project may also be very important. This research deals with the budget allocation problem for the multiple project. This research is unique in that the project scheduling techniques are used for the budgeting problem. Therefore, this research may be used as a strategic decision model for the multiple large projects in public sector.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.134-149
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• 2004

This paper is aimed at proposing a fuzzy inference mechanism to enhancing the quality of cognitive map-based inference. Its main virtue lies in the two mechanisms： (1) a mechanism for avoiding a synchronization problem which is often observed during inference process with traditional cognitive map, and (2) a mechanism for fuzzifying decision maker's subjective judgment. Our proposed fuzzy inference mechanism (FIM) is basically based on the cognitive map stratification algorithm which can stratify a cognitive map into number of strata and then overcome the synchronization problem successfully. Besides, the proposed FIM depends on fuzzy membership function which is administered by decision maker. With an illustrative B2B negotiation problem, we applied the proposed FIM, deducing theoretical and practical implications. Implementation was conducted by Matlab language.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.41-53
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• 2016

Static repositioning is a well-known and commonly used strategy to maximize customer satisfaction in public bike-sharing systems. Repositioning is performed by trucks at night when no customers are in the system. In models that represent the static repositioning problem, the decision variables are truck routes and the number of bikes to pick up and deliver at each rental station. To simplify the problem, the decision on the number of bikes to pick up and deliver is implicitly included in the truck routes. Two relocation-based local search algorithms (1-relocate and 2-relocate) with the best-accept strategy are incorporated into a variable neighborhood search (VNS) to obtain high-quality solutions for the problem. The performances of the VNS algorithm with the effect of local search algorithms and shaking strength are evaluated with data on Tashu public bike-sharing system operating in Daejeon, Korea. Experiments show that VNS based on the sequential execution of two local search algorithms generates good, reliable solutions.

• The Korean Nurse
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• v.19 no.4 s.107
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• pp.51-55
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• 1980

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.123-131
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• 2006

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of low-raking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we are the eigenvector methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.