• Korean Management Science Review
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• v.21 no.3
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• pp.39-54
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• 2004

This paper presents a multi-agent system for intelligent recommendation of travel plans to users. The goal of the system is to provide alternative and preferable travel plans to users when the availability of tickets is low such as in vacations, holidays, weekends, or peak seasons. The multiple agents in the system search for available alternatives for a target travel in collaboration with other agents and recommend best alternatives by analyzing them using a multi-criteria decision-making model. A prototype online travel support system was constructed and a simulation experiment was performed for evaluation and comparison with different travel planning strategies.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.137-140
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• 2003

This paper proposes a pursuing system utilizing the learning method where multiple cooperating agents emulate social behaviors of animals and insects and realize their group behaviors. Each agent contains sensors to perceive other agents in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used fir behavior decision controller. The input of the neural network is decided by the existence of other agents and the distance to the other agents. The output determines the directions in which the agent moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation.

• Journal of Distribution Science
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• v.19 no.11
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• pp.59-68
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• 2021

Purpose: The Covid-19 pandemic has had excessively severe impacts on all the nodes and edges of any supply chain due to changes in consumer behaviours and lockdown restrictions from governments among countries. This article aims to provide a simulating experiment on how a supply chain deals with supply disruption risks by flexibility in the inventory level of each sector as a buffer considering the overall cost to fulfil demand in the market. Research design, data and methodology: Agent-based simulation techniques are used to determine the cost-efficiency and customer waiting time related to varying inventory levels of each member in the supply chain when using inventory buffers. Findings: This study has shown that any sudden changes in the inventory level of each sector are likely to impact the rest of the supply chain. Among all sectors, the wholesaler will be impacted more severely than others. Also, the manufacturing sector is the most suitable node to adjust inventory depending on its manufacturing ability. Conclusion: The findings of the study provide insightful implications for decision-makers to adjust inventory levels and policymakers to maintain manufacturing activities in the context of the pandemic restrictions to deal with the excessive demand and potential supply disruption risks.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.60-66
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• 2016

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2370-2387
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• 2000

This paper proposes a new design strategy that can overcome limitations of two existing approaches, focusing on performance and scalability issues among various architectural issues which must be considered in designing workflow systems. In the proposed approach, we suggest to introduce 'delegation model' which corresponds to the high-level strategy utilizing the fundamental characteristics of mobile agents, after establishing a mobile agent-based workflow system architecture focused on performance and scalability. We point out three major issues that should be considered in this approach and propose a 3-tier mobile agent-based workflow system architecture that effectively reflects these considerations. Also, we show that the new approach can provide better performance and scalability than existing ones - approaches based on the client-server paradigm and other approaches based on mobile agent paradigm represented by DartFlow system - by evaluating performance of the proposed architecture through the GSPN simulation.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.13-24
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• 1996

Workflow is an ordered sequence of interdependent component data activities each of which can be executed on an integrated information system by accessing a remote information system. In our previous research [4], we proposed a distributed CIM Workflow system which consists of a workflow execution model called DAF-Net and an agent-based information systems called AIMIS. Given a component data activity, there needs an interaction protocol among agents which allocates the component data activity to a relevant information systems exist. The objective of this research is to propose and test two protocols: ARR(Asynchronous Request and Response)protocol and NCL(Negotiation with Case based Learning) protocol. To test the effectiveness of the protocols, we applied the PVM(Parallel Virtual Machine) software to simulate the distributed CIM Workflow system. PVM provides a distributed computing environment in which users can run different software processes in different computers while allowing communication among the processes.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.70-77
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• 2014

Collaborative processes among team members including communication, coordination, and information-handling processes either during pre-construction or project execution are required in order to accomplish the objectives of construction projects. However, current construction management practice does not explicitly take the effect of organizational aspects on project performance into account. This paper introduces a method to understand collaborative processes in an explicit and systematic fashion. An agent-based simulation of collaborative working processes within construction project teams was designed from game theory perspective and implemented. The simulation produced both individual behavior and network dynamics. Individuals represented as agents made efforts to improve performance by communication and coordinating with other members, and overall team network was emerged as a result of interactions among members. Interestingly, it was found that the tendency of forming cohesive subgroups increased when sustaining relations with between-group partners incurs higher cost. The primary contribution of this paper is that it presented an explicit approach to examining collaborative working processes in construction project teams and it extended existing computational organization and network studies by integrating individual behavior models and network models.

• Journal of the Korea Society for Simulation
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• v.10 no.1
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• pp.83-92
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• 2001

For the prevention of the network intrusion from damaging the system, both IDS (Intrusion Detection System) and Firewall are frequently applied. The collaboration of IDS and Firewall efficiently protects the network because of making up for the weak points in the each demerit. A model has been constructed based on the DEVS (Discrete Event system Specification) formalism for the simulation of the system that consists of IDS and Firewall. With this model we can simulation whether the intrusion detection, which is a core function of IDS, is effectively done under various different conditions. As intrusions become more sophisticated, it is beyond the scope of any one IDS to deal with them. Thus we placed multiple IDS agents in the network where the information helpful for detecting the intrusions is shared among these agents to cope effectively with attackers. If an agent detects intrusions, it transfers attacker's information to a Firewall. Using this mechanism attacker's packets detected by IDS can be prevented from damaging the network.