### Abstract

A robust simulation-based optimization approach is proposed for truck-shovel systems in surface coal mines to maximize the expected value of revenue obtained from customer trains. To this end, a large surface coal mine in North America is considered as case study, and a highly detailed simulation model of that mine is constructed in Arena. Factors encountered in material handling operations that may affect the robustness of revenue are then classified into 1) controllable, 2) uncontrollable and 3) constant categories. Historical production data of the mine is used to derive probability distributions for the uncontrollable factors. Then, Response Surface Methodology is applied to derive an expression for the variance of revenue under the influence of controllable and uncontrollable factors. The resulting variance expression is applied as a constraint to the mathematical formulation for optimization using OptQuest. Finally, coal production is observed under variation in number of trucks and down events.

Original language | English (US) |
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Title of host publication | Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 |

Pages | 3522-3532 |

Number of pages | 11 |

DOIs | |

State | Published - 2013 |

Event | 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 - Washington, DC, United States Duration: Dec 8 2013 → Dec 11 2013 |

### Other

Other | 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 |
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Country | United States |

City | Washington, DC |

Period | 12/8/13 → 12/11/13 |

### Fingerprint

### ASJC Scopus subject areas

- Modeling and Simulation

### Cite this

*Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013*(pp. 3522-3532). [6721714] https://doi.org/10.1109/WSC.2013.6721714

**Simulation-based robust optimization for complex truck-shovel systems in surface coal mines.** / Nageshwaraniyer, Sai Srinivas; Son, Young-Jun; Dessureault, Sean D.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013.*, 6721714, pp. 3522-3532, 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, Washington, DC, United States, 12/8/13. https://doi.org/10.1109/WSC.2013.6721714

}

TY - GEN

T1 - Simulation-based robust optimization for complex truck-shovel systems in surface coal mines

AU - Nageshwaraniyer, Sai Srinivas

AU - Son, Young-Jun

AU - Dessureault, Sean D

PY - 2013

Y1 - 2013

N2 - A robust simulation-based optimization approach is proposed for truck-shovel systems in surface coal mines to maximize the expected value of revenue obtained from customer trains. To this end, a large surface coal mine in North America is considered as case study, and a highly detailed simulation model of that mine is constructed in Arena. Factors encountered in material handling operations that may affect the robustness of revenue are then classified into 1) controllable, 2) uncontrollable and 3) constant categories. Historical production data of the mine is used to derive probability distributions for the uncontrollable factors. Then, Response Surface Methodology is applied to derive an expression for the variance of revenue under the influence of controllable and uncontrollable factors. The resulting variance expression is applied as a constraint to the mathematical formulation for optimization using OptQuest. Finally, coal production is observed under variation in number of trucks and down events.

AB - A robust simulation-based optimization approach is proposed for truck-shovel systems in surface coal mines to maximize the expected value of revenue obtained from customer trains. To this end, a large surface coal mine in North America is considered as case study, and a highly detailed simulation model of that mine is constructed in Arena. Factors encountered in material handling operations that may affect the robustness of revenue are then classified into 1) controllable, 2) uncontrollable and 3) constant categories. Historical production data of the mine is used to derive probability distributions for the uncontrollable factors. Then, Response Surface Methodology is applied to derive an expression for the variance of revenue under the influence of controllable and uncontrollable factors. The resulting variance expression is applied as a constraint to the mathematical formulation for optimization using OptQuest. Finally, coal production is observed under variation in number of trucks and down events.

UR - http://www.scopus.com/inward/record.url?scp=84894196821&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84894196821&partnerID=8YFLogxK

U2 - 10.1109/WSC.2013.6721714

DO - 10.1109/WSC.2013.6721714

M3 - Conference contribution

SN - 9781479939503

SP - 3522

EP - 3532

BT - Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013

ER -