Yipeng Li, Shuoyan Xu, Lingzi Wu, Simaan M. AbouRizk, Tae J. Kwon, Z. Lei
{"title":"A Generic Simulation Model for Selecting Fleet Size in Snow Plowing Operations","authors":"Yipeng Li, Shuoyan Xu, Lingzi Wu, Simaan M. AbouRizk, Tae J. Kwon, Z. Lei","doi":"10.1109/WSC40007.2019.9004954","DOIUrl":null,"url":null,"abstract":"Accumulated snow on roads poses a threat to traffic systems and rouses significant safety concerns. Snow plowing is often used to recover roads in the event of heavy snow. Due to the unpredictability of weather conditions, it is difficult to determine the overall performance of a certain truck fleet size, thus make it challenging to estimate the number of snow plow trucks needed for a given highway area. The objective of this research is to estimate the truck fleet performance under uncertain weather conditions, and to provide decision support for selecting a reasonable fleet size. A generic simulation model is developed in the Simphony.NET environment. Weather, road network, and truck speed data are entered as inputs, and Monte Carlo simulation is used to generate random snow events to quantify the performance. A case study is developed and presented to demonstrate the practicality and feasibility of the proposed model.","PeriodicalId":127025,"journal":{"name":"2019 Winter Simulation Conference (WSC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC40007.2019.9004954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Accumulated snow on roads poses a threat to traffic systems and rouses significant safety concerns. Snow plowing is often used to recover roads in the event of heavy snow. Due to the unpredictability of weather conditions, it is difficult to determine the overall performance of a certain truck fleet size, thus make it challenging to estimate the number of snow plow trucks needed for a given highway area. The objective of this research is to estimate the truck fleet performance under uncertain weather conditions, and to provide decision support for selecting a reasonable fleet size. A generic simulation model is developed in the Simphony.NET environment. Weather, road network, and truck speed data are entered as inputs, and Monte Carlo simulation is used to generate random snow events to quantify the performance. A case study is developed and presented to demonstrate the practicality and feasibility of the proposed model.