• Korean Journal of Computational Design and Engineering
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• v.19 no.1
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• pp.29-40
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• 2014

Conceptual Modeling is the process of abstracting a model from a real or proposed system. It is probably the most important aspect of a simulation study. Relate works show that the elementary developers devoted little time to understanding how the systems actually worked, namely they didn't build appropriate conceptual model. Thus, the result of simulation is inconsistent because it depends on developer's competence. Although many researchers suggested various techniques enabling developer to build conceptual model, there were several limitations. In this study, to overcome the limitations of existing techniques, we proposed COMBINE-DES (COnceptual Model BuildINg framEwork using ontology for Discrete Event Simulation). The COM-BINE-DES supports expediting the conceptual modeling with Solution ontology generated by Domain ontology and Simulation ontology. Moreover, it provides consistent simulation result regardless of repeated modeling.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.29-37
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• 2009

This paper deals with the priority queues exploited for the management of future event list in discrete event simulation. Among several implementations of priority queues, MList which consists of 3 tiers has been known to reveal the good performance. To improve the performance of MList, Dynamic-Shift MList (DSMList) is proposed in this paper. Whenever the number of events in tier 3 exceeds a critical number, DSMList creates new calendar queue in tier 2, then moves events from Tier 3 to the calendar queue. Instead of one calendar queue, therefore, a number of calendar queues are dynamically created in tier 2. Throughout experiments for the performance evaluation of DSMList, it shows that at least 20% improvement is obtained compared with MList.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Journal of the Korea Society for Simulation
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• v.2 no.1
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• pp.31-44
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• 1993

Zeigler's DEVS(Discrete Event Systems Specification) formalism supports formal specification of discrete event systems in a hierarchical , modular manner. Associated are hierarchical, distributed simulation algorithms, called abstract simulators, which interpret dynamics of DEVS models. This paper deals with performance evaluation of P-DEVSIM ++, a parallel simulation environment which implements the DEVS formalism and associated simulation algorithms in a parallel environment. Performance simulator has been developed and used to experiment models of parallel simulation executions in different conditions. The experimental result shows that simulation time depends on both the number of processors in the parallel system and the communication overheads among such processors.

• Korean Journal of Computational Design and Engineering
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• v.13 no.1
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• pp.67-75
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• 2008

In spite of rapidly increasing interests in digital manufacturing, there still lacks of a systematic approach in manufacturing line flow analysis via modeling and simulation; currently, the parameters for designing manufacturing line are defined by being solely based on engineers experiences. The paper proposes an application of the genetic algorithm to a discrete event line simulation finding optimal set of parameters for manufacturing line balancing problem. The proposed method has been applied to two example problems-one is a simple manufacturing model and the other for shipyard industry-in order to demonstrate its validity and usefulness.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.1
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• pp.83-101
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• 2016

This paper suggests an event-based scenario manager capable of creating and editing a scenario for shipbuilding process simulation based on multibody dynamics. To configure various situation in shipyards and easily connect with multibody dynamics, the proposed method has two main concepts: an Actor and an Action List. The Actor represents the anatomic unit of action in the multibody dynamics and can be connected to a specific component of the dynamics kernel such as the body and joint. The user can make a scenario up by combining the actors. The Action List contains information for arranging and executing the actors. Since the shipbuilding process is a kind of event-based sequence, all simulation models were configured using Discrete EVent System Specification (DEVS) formalism. The proposed method was applied to simulations of various operations in shipyards such as lifting and erection of a block and heavy load lifting operation using multiple cranes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.816-819
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• 1996

This paper focuses on development of simulation model for SAE J1850 and performance evaluation of a J1850 network. The simulation model has been developed by using discrete event simulation language. SAE J1850 is one of Class B network protocol for general data sharing applications. Through numerous simulation experiments, several important performance factors such as the probability of a successful transmission, average queue delay, and throughput have been evaluated.

• Journal of the Korea Society for Simulation
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• v.6 no.1
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• pp.1-13
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• 1997

In this paper, we present a partitioning algorithm for distributed simulation of DEVS (Discrete Event System Specification) models. To preserve concurrency inherent in models, the proposed algorithm utilizes the structural information of models. Through benchmark simulation experiments, we show that the proposed algorithm can generate good partitions.

• Journal of the Korea Society for Simulation
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• v.20 no.1
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• pp.87-96
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• 2011

DEVS(Discrete Event Systems Specification) is a set theoretic formalism developed for specifying discrete event system. For execution of DEVS, we need an execution environment, which consists of simulation engine and models interpreted by the simulation engine. Common existing environments use hierarchical scheduling algorithm for DEVS execution. This hierarchical scheduling is a proper algorithm for DEVS execution because of hierarchical and modular characteristics. But this algorithm has overheads owing to message passing and time management. To overcome these overheads, we apply event-oriented simulation to DEVS execution and we remove hierarchical overheads. In eventoriented simulation, the scheduling of model execution is performed by events and event list. We propose three event-oriented execution environments for DEVS and experiment about the performance of our proposed environments in comparison with the existing execution environment using the hierarchical scheduling. The experimental results show our environments works better than existing environment using the hierarchical scheduling.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.9-17
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• 2006

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.