• ETRI Journal
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• v.44 no.2
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• pp.313-326
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• 2022

This study presents a noble scheme for distributed and parallel simulations with optimized agent placement for simulation instances. The traditional parallel simulation has some limitations in that it does not provide sufficient performance even though using multiple resources. The main reason for this discrepancy is that supporting parallelism inevitably requires additional costs in addition to the base simulation cost. We present a comprehensive study of parallel simulation architectures, execution flows, and characteristics. Then, we identify critical challenges for optimizing large simulations for parallel instances. Based on our cost-benefit analysis, we propose a novel approach to overcome the performance constraints of agent-based parallel simulations. We also propose a solution for eliminating the synchronizing cost among local instances. Our method ensures balanced performance through optimal deployment of agents to local instances and an adaptive agent placement scheme according to the simulation load. Additionally, our empirical evaluation reveals that the proposed model achieves better performance than conventional methods under several conditions.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.453-458
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• 2001

A mobile agent is an autonomous software agent capable of moving from one computer to another while performing its tasks. We view the agent as a discrete event system in the view of its computation and communication. This paper presents a methodology far modeling and simulation of such a mobile agent system as a discrete event system. The methodology is based on the Mobile Discrete Event System Specification (MDEVS) formalism and the associated simulation environment AgentSim which are previously developed by the authors. Within the methodology an atomic model represents dynamics of a mobile agent; a coupled model is modeled as mobile agent servers for representation of structural changes between atomic agents. Being based on the object-oriented environment the modeling methodology exploits inheritance of basic classes AtomicModel and CoupledModel provided by AgentSim.

• 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.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1359-1363
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• 2009

The object of this research is to develop a simulation system for earthmoving operations in consideration of the impact of congestion in-between equipment and existing traffic flow around the site. The congestion in-between equipment and traffic flow affect work productivity. The conventional discrete event simulation, however, has limitations in simulating the flow of construction equipment. To consider the impact of congestion in-between equipment and existing traffic flow, in this paper, a multi-agent based simulation model that can realize characteristics of truck behavior more accurately to consider the impact of congestion was proposed. In this simulation model, multiple agents can identify environmental changes and adapt themselves to the new environment. This modeling approach is a better choice for this problem since it describes behavioral characteristics of each agent by sensing changes in dynamic surroundings. This study suggests a detailed system design of the multi-agent based simulation system.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.629-641
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• 2021

Crowd behavior simulations have been studied to further accelerated and refined by parallelism by inducing agent-interacting forces into the image field representing the forces of attraction and repulsion. However, it was difficult to consider rapidly changing environments such as fire situations in buildings because texture images must be generated in advance simulation starts and simulations can only be performed in 2D spaces. In this paper, we propose a crowd agent behavior simulation method based on agent's 3D affordance field for flexible agent behavior in variable geomorphological environments in 3D space. The proposed method generates 3D affordance field related to agents and sensors in 3D space and defines the agent behavior in 3D space for the crowd behavior simulation based on an image-inducing field to a 3D space. Experimental results verified that our method enables the development of large-scale crowd behavior simulations that are flexible to various fire evacuation situations in 3D virtual spaces.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.439-444
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• 2011

As construction projects have been getting larger and more complex, a single individual or organization cannot have complete knowledge or the abilities to handle all matters. Collaborative practices among heterogeneous individuals, which are temporarily congregated to carry out a project, are required in order to accomplish project objectives. These organizational knowledge creation processes of project teams should be understood from the active and dynamic viewpoint of how they create information and knowledge rather than from the passive and static input-process-output sequence. To this end, agent-based modeling and simulation which is built from the ground-up perspective can provide the most appropriate way to systematically investigate them. In this paper, agent-based modeling and simulation as a research method and a medium for representing theory is introduced. To illustrate, an agent-based simulation of the evolution of collaboration in large-scale project teams from a game theory and social network perspective is presented.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.1-9
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• 2019

An agent-based simulation is a popular simulation tool to solve various problems, such as stock market, population prediction, disease prediction, and development of a traffic system. As the agents are developed and researched in different application fields, the agent has a rigid structure and may not acceptable in different domains. As a result, it is a challenging problem to define a structure for an agent structure to reflect the researcher's simulation objective. This research proposes an extendable form for an agent and its modeling environment. In order to propose a standard structure, this study adopts system entity structure and discrete event system specification formalism. Also, this research introduces the SESManager which supports the proposed specification method. The proposed environment can hierarchically define the agent structure and synthesize the agent so that it can perform the agent simulation according to the user's simulation purpose.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.27-34
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• 2012

Proposed in the paper is an agent based and object-oriented methodology to create a virtual logistics support system model. The proposed virtual logistics support system model consists of three types of objects: the logistics force agent model(static model), the military supplies transport manager model(function model), the military supplies state manager model(dynamic model). A logistic force agent model consists of two agent: main function agent and function agent. To improve the reusability and composability of a logistics force agent model, the function agent is designed to adapt to different logistics force agent configuration. A military supplies transport manager is agent that get information about supply route, make decisions based on decision variables, which are maintained by the military supplies state manager, and transport military supplies. A military supplies state manager is requested military supplies from logistics force agent, provide decision variables such as the capacity, order of priority. For the implementation of the proposed virtual logistics force agent model, this paper employs Discrete Event Systems Specification(DEVS) formalism.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.588-598
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• 2015

In this paper, a simulation model for assessing the impact of alternative field service engineer replenishment policies is introduced. The end-to-end supply chain simulation model is created using a discrete-event and agent-based simulation model, which enables accurate description of key individual entities in the investigated supply chain, such as field service engineers. Once the model is validated with the historical data, it is used to assess the impacts of field service engineer replenishment policies for a major printing equipment manufacturing firm.In the case study, newly proposed replenishment policies for post-sale distribution supply chain are assessed for the level of service improvement to end customers.

• Korean System Dynamics Review
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• v.7 no.1
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• pp.27-49
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• 2006

A system dynamics model is developed to investigate the applicability of the agent based modeling concept in the system dynamics model. The assumed problem is to forecast the size and structure of the organization with the developing market environment. The agent based modeling concept is applied to the organization part, and the other parts of the model such as market, facilities, etc. are developed with the traditional system dynamics technique. The simulation results show the agent based modeling part can be combined with the traditional system dynamics modeling with more precisions. However, the complexity increases and the simulation times are longer than those of the traditional method.