Demand Forecast and Multi-Objective Ambulance Allocation

doi:10.1142/S0218001418590115

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/115494

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题名:	Demand Forecast and Multi-Objective Ambulance Allocation
作者:	Tsia, Yihjia;Chang, Kuan-Wu;Yiang, Giou-Teng;Lin, Hwei Jen
关键词:	Demand forecast;emergency medical services;qradtree decomposition;particle swarm optimization;ambulance allocation model
日期:	2018-01-24
上传时间:	2018-11-01 12:10:55 (UTC+8)
出版者:	World Scientific
摘要:	This study considers the two-fold dynamic ambulance allocation problem, which includes forecasting the distribution of Emergency Medical Service (EMS) requesters and allocating ambulances dynamically according to the predicted distribution of requesters. EMSs demand distribution forecasting is based on on-record historical demands. Subsequently, a multi-objective ambulance allocation model (MOAAM) is solved by a mechanism called Jumping Particle Swarm Optimization (JPSO) according to the forecasted distribution of demands. Experiments were conducted using recorded historical data for EMS requesters in New Taipei City, Taiwan, for the years 2014 and 2015. EMS demand distribution for 2015 is forecasted according to the on-record historical demand of 2014. Ambulance allocation for 2015 is determined according to the anticipated demand distribution. The predicted demand distribution and ambulance allocation solved by JPSO are compared with historic data of 2015. The comparisons verify that the proposed methods yield lower forecasting error rates and better ambulance allocation than the actual one.
關聯:	International Journal of Pattern Recognition and Artificial Intelligence 32(7),p.1-21
DOI:	10.1142/S0218001418590115
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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