• Management Science and Financial Engineering
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• v.10 no.1
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• pp.1-23
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• 2004

The changing structure of organization and the increasing diversity of business have forced organizations to have abilities to coordinate dispersed business activities. They have required cooperation and coordination among the functional units in the organization which should involve group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative process of group decision-making, they often lack the features supporting the dynamic complexity issue frequently occurring at group decision-making processes. This results in cognitive unfit between the group decision-making tasks and their supporting tools, bringing about mixed results in their effects on group decision-making. This study proposes system dynamics modeling as a group decision-making support tool to deal with the group decision -making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Journal of the Korea Society for Simulation
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• v.12 no.1
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• pp.49-58
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• 2003

There have been growing recognition on the needs of coordination of diverse activities across cross-functional business areas necessarily involving group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative processes of group decision-making, they often lack features supporting the dynamic complexity issues. This study proposes system dynamics modeling approach based on simulation techniques to deal with the group decision-making tasks having properties of dynamic complexity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.958-965
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• 2003

The rapidly changing business environment has required cooperation and coorduiation among functional units n organizations which should Involve group decision-making processes Although many group derision-making support tools and methods have provided the collaborative capabilities for organizational members, they often lack features supporting the dynamic complexity issue frequently occurring at group decision-making processes This study proposes system dynamics modeling as a group decision-making support tool to deal with the group derision-making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.327-331
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• 2009

In fuzzy logic, aggregating uncertainties is generally achieved by means of operators such as t-norms and t-conorms. However, existing aggregation operators have some disadvantages as follows : First, they are situation-independent. Thus, they may not be properly applied to dynamic aggregation process. Second, they do not give an intuitional sense to decision making process. To solve these problems, we propose a new $\varepsilon$-AMDA (Aggregation based on the fuzzy Multidimensional Decision Analysis) algorithm to reflect degrees of strength for option i (i = 1, 2, ..., n) in the decision making process. The $\varepsilon$-AMDA algorithm makes adaptive aggregation results between min (the most weakness for an option) and max (the most strength for an option) according to the values of the parameter representing degrees of strength for an option. In this respect, it may be applied to dynamic aggregation process. In addition, it provides a mechanism of the fuzzy multidimensional decision analysis for decision making, and gives an intuitional sense to decision making process. Thus, the proposed method aids the decision maker to get a suitable decision according to the degrees of strength for options (or alternatives).

• Journal of KIISE
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• v.43 no.7
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• pp.801-811
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• 2016

Self-adaptive systems (SASs) can change their goals and behaviors to achieve its ultimate goal in a dynamic execution environment. Existing approaches have designed, at the design time, utility functions to evaluate and predict the goal satisfaction, and set policies that are crucial to achieve each goal. The systems can be adapted to various runtime environments by utilizing the pre-defined utility functions and policies. These approaches, however, may or may not guarantee the proper adaptability, because system designers cannot assume and predict all system environment perfectly at the design time. To cope with this problem, this paper proposes a new method of dynamic decision making, which takes the following steps: firstly we design a Dynamic Decision Network (DDN) with environmental data and goal model that reflect system contexts; secondly, the goal satisfaction is evaluated and predicted with the designed DDN and real-time environmental information. We furthermore propose a dynamic reflection method that changes the model by using newly generated data in real-time. The proposed method was actually applied to ROBOCODE, and verified its effectiveness by comparing to conventional static decision making.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.37-44
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• 2014

In this paper, we propose a NPC decision making model based on Prospect Theory which tries to model real-life choice, rather than optimal decision. For this purpose, we analyse the problems of reference point setting, diminishing sensitivity and loss aversion which are known as limitations of the utility theory and then apply these characteristics into the decision making in game. Dynamic Terrain Analysis is utilized to evaluate the proposed model and experimental result shows the method have effects on inducing diverse personality and emergent behavior on NPC.

• Proceedings of the Korea Association of Information Systems Conference
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• 2003.05a
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• pp.241-251
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• 2003

The rapidly changing environment have forced organizations to improve systems thinking capability to coordinate diverse activities across cross-functional business areas necessarily involving group decision-making processes. Although many approaches have been introduced to enable the collaborative processes of group decision-making, they often lack features supporting the dynamic complexity issues. The study proposes system dynamics modeling based on simulation techniques to improve systems thinking capability in group decision-making context.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.1-11
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• 2017

Stochastic resource-constrained project scheduling problem is an extension of resource-constrained project scheduling problem such that activity duration has stochastic nature. In real situation where activity duration is not known until the activity is finished, open-loop based static policies such as activity-based policy and priority-based policy will not well cope with duration variability. Then, a dynamic policy based on closed-loop decision making will be regarded as an alternative toward achievement of minimal makespan. In this study, a dynamic policy designed to select activities to start at each decision time point is illustrated. The performance of static and dynamic policies based on variable neighborhood search is evaluated under the discrete-event simulation environment. Experiments with J120 sets in PSPLIB and several probability distributions of activity duration show that the dynamic policy is superior to static policies. Even when the variability is high, the dynamic policy provides stable and good solutions.

• Korean Journal of Construction Engineering and Management
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• v.7 no.3 s.31
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• pp.45-55
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• 2006

This study aims need set of mind to construction manager built a theory logic conceive decision making system and principles designed to create the administrative procedures that a company needs to integrate management and environmental concerns into its daily business practices. Integrate considerations of risk reduction and wise resource management into daily business decision making environmental that includes performance and cost. Seek to make better Dynamic time solutions that promote competitiveness set of management mind provide business with tools and methodologies management participation, psychology, philosophy effects of resource flows. A last of understand use of the decision making element principal as a guideline for evaluating and ranking approaches. The result of this study are summarized as follows; (1) setting for approach decision making of manager police, (2) dynamic of time and management mind (3) a primary factor out environment to decision making (4) methodologies of set up system for management mind (5) expectation effect of management mind.