How to Build Valid and Credible Simulation Models

Law, Averill M.

doi:10.1109/wsc40007.2019.9004789

Cited by 107 publications

(53 citation statements)

References 5 publications

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“…To accomplish the purposes of this study in an efficient way, a structured methodology is followed, based on the work of [35]- [37]. This methodology can be summarized as followed (See Figure 1):  Problem formulating: Define the objectives and the perimeter of the study and clarify the functioning of the system.…”

Section: Methodsmentioning

confidence: 99%

A Proposed Budgeting Planning Model for Bimodal Transportation in a Phosphate Supply Chain

Azougagh*,

Benhida,

Elfezazi

et al. 2019

IJRTE

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To better understand supply chain behavior and to evaluate its performance, it is necessary to start a modeling process. For this purpose, various tools and approaches are used. Among these tools, the analytical models can be used. With this background, the purpose of this study is proposition of a generic model for the transportation budgeting planning problems in multi-sites, multi-products, multi-depots and multi-periods context. The main contribution of this paper is to develop an integrated budgeting planning model (Mixed Integer Programming) applied in a phosphate supply chain. The purpose of the developed model is to define the optimum transportation budget of products routed in the various entities of the studied supply chain, considering various constraints (Capacity of facilities, availability of product and transportation vehicles, customers demand…) in order to plan and define the optimum products quantities and the optimize the costs to feed stocks and satisfy customers.

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Section: Methodsmentioning

confidence: 99%

A Proposed Budgeting Planning Model for Bimodal Transportation in a Phosphate Supply Chain

Azougagh*,

Benhida,

Elfezazi

et al. 2019

IJRTE

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“…Dessa forma, assume-se a inexistência de mudanças no sistema entre os eventos modelados. Mesmo em caso de haver incrementos fixos de avanço no tempo, o que não é muito comum, a evolução do sistema não ocorre de forma contínua no tempo, mas sim discreta (Law, 2006).…”

Section: 1simulação a Eventos Discretosunclassified

Estruturação e aumento da OEE em uma linha de produção de uma Indústria de Nutrição Animal

Almeida¹,

Mattera²,

Júnior³

et al. 2020

Gestão Da Produção Em Foco - Volume 39

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“…Overall, a simulation model is usually a simplification and approximation of the real system. “There is no such thing as absolute model validity, nor is it even desired” 50 (p. 24).…”

Section: Case Studymentioning

confidence: 99%

“…The p -value quantifies the confidence about this decision and the UTASiMo-generated model was considered valid for the acceptable range of accuracy under the given set of the experimental conditions. 50 However, two types of errors need to be taken into consideration when using this validation method: Type I error (or model builder’s risk) and Type II error (or model user’s risk). Type I error is the incorrect rejection of a true null hypothesis and the probability of making it is α = 0.05, while a Type II error is incorrectly retaining a false null hypothesis and the probability of making a Type II error is β≈ 0.016.…”

Section: Case Studymentioning

confidence: 99%

UTASiMo: a simulation-based tool for task analysis

Angelopoulou

Mykoniatis

2017

SIMULATION

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Research on task analysis and human performance has focused on the development of adequate tools, models, and methods to understand, analyze, and improve the relationship between humans and systems. As technology continues to advance and to change the nature of human work, techniques of analysis are changing to meet the new needs. This work attempts to fill the gaps in the current task analysis tools and describes the architecture and development of a simulation model, named UTASiMo. UTASiMo is a simulation tool that aims to enhance task analysis by automatically generating a multi-method simulation model for well-defined tasks based on a spreadsheet template filled in by the user. The generated model analyzes and simulates tasks performed by individual simulated agents representing human operators while accounting for the estimation of an operator's utilization and error prediction. This work highlights the design, development, and evaluation of the hybrid architecture (discrete event and agent based) of UTASiMo. The development of the system dynamics model, which is responsible for the human error assessment, is a work in progress and is excluded from the present paper. A real-world case study has been adapted to evaluate the hybrid architecture of UTASiMo. The same case study was modeled using the Micro Saint simulation tool. The results produced by UTASiMo were compared with the real-world data as well as with the results produced by Micro Saint for validation purposes. The comparisons indicate the validity of the UTASiMo-generated model and also that the hybrid architecture produces more variability in the results than using only one method. The comparisons also show promise that the tool will reduce the time and effort of the task analysis simulation.

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How to Build Valid and Credible Simulation Models

Cited by 107 publications

References 5 publications

A Proposed Budgeting Planning Model for Bimodal Transportation in a Phosphate Supply Chain

A Proposed Budgeting Planning Model for Bimodal Transportation in a Phosphate Supply Chain

Estruturação e aumento da OEE em uma linha de produção de uma Indústria de Nutrição Animal

UTASiMo: a simulation-based tool for task analysis

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