Colored Petri Net Simulation Model to Allocate Motor Graders for Earthmoving Operations

Rodrigues, Mateus Oliveira; Prata, Bruno de Athayde; Barroso, Giovanni Cordeiro; Júnior, Ernesto Ferreira Nobre; Oliveira, Francisco Heber Lacerda de

doi:10.1061/jpeodx.0000079

Cited by 2 publications

(1 citation statement)

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“…While the accuracy of the DES model relies on accurate prediction of the duration of the four activities, predicting the duration of loading activities is challenging, since it is affected by multiple factors (e.g., weather conditions, soil conditions) and changes over time. The duration of loading activities has traditionally been determined as a probabilistic distribution using historical data (Rodrigues et al 2018;Krantz et al 2019). However, using this approach, the effects of the different factors influencing the duration of this activity are not explicitly accounted for but are instead implicit in the probabilistic distributions.…”

Section: R a F Tmentioning

confidence: 99%

Modeling earthmoving operations in real time using hybrid fuzzy simulation

Seresht

Fayek

2022

Can. J. Civ. Eng.

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Predicting and optimizing performance in earthmoving operations is critical, because they are essential to many construction projects. The complexity of modeling earthmoving operations remains challenging, even with several modeling techniques available, including simulation. This paper advances the state-of-the-art of modeling earthmoving operations by introducing a hybrid fuzzy system dynamics–discrete event simulation framework with the capacity to: capture the dynamism of performance in earthmoving operations; capture subjective uncertainty of several factors affecting them; model their sequential nature and resource constraints; and determine actual travel time, in real time, using online navigation systems. Findings from this research confirm the proposed framework (1) extends the application of simulation techniques for modeling construction processes involving dynamic input variables and subjective uncertainty, through its ability to capture the non-probabilistic uncertainty of construction systems, and (2) when combined with the use of online navigation systems to assess trucks’ travel time, improves the accuracy of earthmoving operation models.

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Section: R a F Tmentioning

confidence: 99%