• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.101-114
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• 2018

Several different approaches and mechanisms are introduced to solve the UAV path planning problem. In this paper, we designed and implemented an agent-based simulation software using the Repast platform and Java Genetic Algorithm Package to examine an evolutionary path planning method by implementing and testing within the Repast environment. The paper demonstrates the life-cycle of an agent-based simulation software engineering project while providing a documentation strategy that allows specifying autonomous, adaptive, and interactive software entities in a Multi-Agent System. The study demonstrates how evolutionary path planning can be introduced to improve cognitive agent capabilities within an agent-based simulation environment.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.159-166
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• 2012

A*algorithm is highly useful to search the shortest route to the destination in the evacuation simulation. For this reason, A*algorithm is used to evaluate the evacuation experiment by the computer simulation. However there are some problems to analyze the outcome in relation to the reality. Because all the people in the building are not well-informed of the shortest route to the exit. And they will not move to the disaster spot though it is shortest route to the exit. Therefore, evacuation simulation program based on A*algorithm raise a problem of bottleneck phenomenon and dangerous result by damage surrounding the disaster spot. The purpose of this research is to prove the necessity for dispersion evacuation simulation by Multi agent system to solve the problems of the existing evacuation simulation program based on A*algorithm.

• Asia pacific journal of information systems
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• v.14 no.4
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• pp.49-70
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• 2004

Multi-agent technology is being regarded as one of the promising technologies for today's supply chain management because of its desirable features such as autonomy, intelligence, and collaboration. This paper suggests a multi-agent system architecture with which companies can improve the efficiency of their supply chains by collaborative operation. Reflecting the practical difficulties of collaboration in complex supply chains, the architecture allows agent systems to share information with only neighboring companies for the coordinated operation. The suggested architecture is elaborated with a collaboration model based on Petri-net, conversation models for communication, and internal behavior models of each agent. A simulation experiment was performed for the evaluation of the suggested architecture. The result implies that when the estimation of market demand is higher than a certain level, the suggested architecture can be beneficial.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.117-125
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• 2009

Recently the intelligent agent systems have been emerged as one of key issues for developing the defense M&S systems. However, most conventional agent architecture of M&S systems utilize the script-based models and can only deal with the individual behaviors so that they cannot suitably describe the precise tactical/strategic behavior and/or complex warfare environment. To overcome these problems, we have proposed the hierarchical multi-agent system architecture that is able to intelligently cope with the complex missions based on the functional role of each agent on the hierarchy such as an intelligence officer, captain, warship commander. Several simulation tests performed on 2:2 warship warfare models will illustrate our techniques.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.75-83
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• 2014

Most warship combat systems inquire human operator to control several sensor and another equipments as well as decision-modeling. For this reason, many researches with multi-agent based M&S (Modeling and Simulation) have been increasingly conducted. However there cannot find any researches of M&S based analysis for anti-submarine warfare that requires a high level of mission complexity between multiple platforms. In this research, we have been developed various combat platform models such as warship, submarine and helicopter, etc. In order to apply the multi-agent-based M&S technology to the anti-submarine warfare i.e. a HVU (High Value Unit) escort mission scenario. Then we have successfully analyzed the measures of effectiveness according to the different tactics and different situations. In future, the defence engineer maybe employ our methodology and tools to analyze actual tactical problem by simply inserting actual data into our agent model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.107-114
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• 2017

In general, credibility for some analysis results is very important to most decision makers. Especially, it is even more critical for military commander to choose the best course of action by using the simulation results when he want to decide to allocate his available weapon system assets. Therefore, improving the credibility of simulation output is one of the key issues in military research fields. In this paper, we proposed a new simulation framework to improve the credibility of weapon's effectiveness analysis results. Multi-agent based simulation tool is applied and compare current process to the proposed framework. We also showed an example case when a communication repeaters are installed to expand the commanding area scope. The example clearly tells why this new simulation framework is more efficient and improve the credibility of simulation results.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.625-631
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• 2011

This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.167-173
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• 2019

This study investigates the problem of leader-following consensus for multi-agent systems with output saturations. This study assumes that the agents are described as a neutrally stable system, and the leader agent generates the bounded trajectory within the saturation level. Then, the objective of the leader-following consensus is to track the trajectory of the leader by exchanging information with neighbors. To solve this problem, we propose an observer-based distributed consensus algorithm. Then, we provide a consensus analysis by applying the Lyapunov stability theorem and LaSalle's invariance principle. The result shows that the agents achieve the leader-following consensus in a global sense. Moreover, we can achieve the consensus by choosing any positive control gain. Finally, we perform a numerical simulation to demonstrate the validity of the proposed algorithm.

• Journal of Information Technology Services
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• v.18 no.3
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• pp.17-35
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• 2019

Call centers do not simply play a role of responding to customers' calls, but they have developed into a core unit for maintaining competitiveness through services, marketing, or sales. Since the service quality of call centers heavily affects customer satisfaction, organizations have focused on enhancing it by reducing waiting time and increasing service level. One of the techniques, which improve the service quality of call centers, is to employ multi-skilled agents that can handle more than one type of calls. This study deals with three issues relevant to multi-skilled agents. First, we analyze how the way of allocating a specific group of agents to a set of skills affects the performance of call centers. Secondly, we investigate the relationship between the number of multi-skilled agents and the performance of call centers. Finally, we examine the impact of agent selection rules on the performance of call centers. Two selection rules are compared : the first rule is to assign a call to any available agent at random while the other rule is to assign a call preferably to single-skilled agents over multi-skilled agents when applicable. Based on simulation experiments, we suggest three implications. First, as the length of cycles in the agent-skill configuration network becomes longer, call centers achieve higher service level and shorter waiting time. Secondly, simulation results show that as the portion of multi-skilled agents increases, the performance of call centers improves. However, most of the improvement is attained when the portion of multi-skilled agents is relatively low. Finally, the agent selection rules do not significantly affect the call centers' performance, but the rule of preferring single-skilled agents tends to distribute the workload among agents more equally.