Web Services-Based Parallel Replicated Discrete Event Simulation for Large-Scale Simulation Optimization

Yoo, Taesik; Cho, Hyunbo; Yücesan, Enver

doi:10.1177/0037549709106340

Cited by 12 publications

(9 citation statements)

References 43 publications

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“…Gyimesi (2008) proposed a Web Services based framework for generic DES. More recently, using Web Services based SBO through the distribution of simulation replications across different servers was presented by Yoo et al (2009). Their focus was on using an Optimal Computing Budget Allocation (OCBA) to allocate different number of simulation replications to different servers to improve the overall execution efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation

Ng¹,

Bernedixen²,

Moris³

et al. 2011

Proceedings of the 2011 Winter Simulation Conference (WSC)

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Despite simulation offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory flow design. If simulation is used today for system design, it is more often used in later phases when important design decisions have already been made and costs are locked. With an aim to advocate the use of simulation in early phases of factory design and analysis, this paper introduces FACTS Analyzer, a toolset developed based on the concept of integrating model abstraction, automatic model generation and simulation-based optimization under an innovative Internet-based platform. Specifically, it addresses a novel model aggregation and generation method, which when combined together with other system components, like optimization engines, can synthetically enable simulation to become much easier to use and speed up the time-consuming model building, experimentation and optimization processes, in order to support optimal decision making. INTRODUCTIONReal-world systems in manufacturing, supply chains and public services are too complex to be modeled by analytical techniques. Therefore, discrete event simulation (DES) are very useful for performing modeling and analysis on these systems. However, DES models are by nature evaluative -instead of suggesting any optimal solutions, a DES model evaluates a given set of design variables and generates the required performance measures. For a decision maker, the process of finding a sufficiently good design setting could be too time-consuming and in many cases impossible if the search space is huge. Simulation-based optimization (SBO) is a relatively new technique applied to seek the "optimal" setting for a complex system based on one or multiple performance measures generated from simulation by using various searching methodologies. SBO is a technology that offers huge potentials to solve real-world problems and have been successfully applied in many different domains (April et al. 2004). Nevertheless, until now, virtually all of today's commercial SBO packages still possess several major limitations: (1) they work in a deterministic mode, without taking into account the stochastic outputs from DES; (2) they do not explicitly address multi-objective problems, and (3) similar to most of the DES packages, the majority of SBO tools available is traditional software that need to be installed and run locally on the users' computers. With the vision that Internet and Web technologies could enable the explosive growth in research and commercial opportunities (Fu et al. 2000;Boesel et al. 2001;Miller et al. 2001), many efforts have been paid on Web-based simulation (WBS) since the 1990s. However, as summarized recently by Byrne 2176 978-1-4577-2109-0/11/$26.00 ©2011 IEEE

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Section: Literature Reviewmentioning

confidence: 99%

Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation

Ng¹,

Bernedixen²,

Moris³

et al. 2011

Proceedings of the 2011 Winter Simulation Conference (WSC)

View full text Add to dashboard Cite

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“…A more recent study on web-based simulation-optimization is presented by Yoo et al (2009). The design of this platform, which is implemented partly using Java and partly using the .NET framework, is shown in Figure 2 (freely from Yoo et al, 2009).…”

Section: Simulation Client Simulation Clientmentioning

confidence: 99%

“…The design of this platform, which is implemented partly using Java and partly using the .NET framework, is shown in Figure 2 (freely from Yoo et al, 2009). The platform is similar to the one proposed by Luo et al (2000) in that both implement an OCBA-based optimization algorithm and a distributed architecture for parallel simulation evaluations.…”

Section: Simulation Client Simulation Clientmentioning

confidence: 99%

“…The database has a web interface which allows communication over the internet. Yoo et al (2009) evaluate their proposed platform using a theoretical AGV control problem. However, the evaluation is only performed with respect to optimization algorithm behavior, and only a general discussion of the web-based aspects of the platform is provided.…”

Section: Simulation Client Simulation Clientmentioning

confidence: 99%

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A web-based platform for the simulation–optimization of industrial problems

Syberfeldt

Karlsson

et al. 2013

Computers & Industrial Engineering

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A web-based platform for the simulation-optimization of industrial problems. Computers & industrial engineering, 64(4): AbstractThis study presents a platform for industrial, real-world simulation-optimization based on web techniques. The design of the platform is intended to be generic and flexible and thereby make it possible to apply the platform in various problem domains. In the implementation of the platform, modern web techniques, such as Ajax, JavaScript, GWT, and ProtoBuf, are used. The platform is tested and evaluated on a real industrial problem of production optimization at Volvo Aero Corporation, a company that develops and manufactures high-technology components for aircraft and gas turbine engines. The results of the evaluation show that while the platform has several benefits, implementing a web-based system is not completely straightforward. At the end of the paper, possible pitfalls are discussed and some recommendations for future implementations are outlined.

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“…Algorithms that solve SO problems on finite sets can broadly be characterized as class :J> procedures, which provide a finite-time probabilistic guarantee on the solution quality, and class ;:, procedures, which tend to provide guarantees on simulation efficiency (Pasupathy and Ghosh 2013). While parallel versions of class;:' procedures have been explored (Luo et al 2000;Yoo, Cho, and Yiicesan 2009), we further narrow our focus in this paper to parallel class :J> procedures that provide a finite-time guarantee. That is, we broadly focus on procedures that, upon completion, return the "best" system with probability greater than 1-a when the best system is at least o-better than the second-best for user-specified parameters a and O.…”

Section: Introductionmentioning

confidence: 99%

A comparison of two parallel ranking and selection procedures

Ni¹,

Henderson²,

Hunter³

2014

Proceedings of the Winter Simulation Conference 2014

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Traditional solutions to ranking and selection problems include two-stage procedures (e.g., the NSGS procedure of Nelson et al. 2001) and fully-sequential screening procedures (e.g., Hong 2006). In a parallel computing environment, a naively-parallelized NSGS procedure may require more simulation replications than a sequential screening procedure such as that of Ni, Hunter, and Henderson (2013) (NHH), but requires less communication since there is no periodic screening. The parallel procedure NHH may require less simulation replications overall, but requires more communication to implement periodic screening. We numerically explore the trade-offs between these two procedures on a parallel computing platform. In particular, we discuss their statistical validity, efficiency, and implementation, including communication and load-balancing. Inspired by the comparison results, we propose a framework for hybrid procedures that may further reduce simulation cost or guarantee to select a good system when multiple systems are clustered near the best.

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Web Services-Based Parallel Replicated Discrete Event Simulation for Large-Scale Simulation Optimization

Cited by 12 publications

References 43 publications

Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation

Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation

A web-based platform for the simulation–optimization of industrial problems

A comparison of two parallel ranking and selection procedures

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