Models for ambulance planning on the strategic and the tactical level

Ambulance planning involves decisions to be made on different levels. The decision for choosing base locations is usually made for a very long time (strategic level), but the number and location of used ambulances can be changed within a shorter time period (tactical level). We present possible formulations for the planning problems on these two levels and discuss solution approaches that solve both levels either simultaneously or separately. The models are set up such that different types of coverage constraints can be incorporated. Therefore, the models and approaches can be applied to different emergency medical services systems occurring all over the world. The approaches are tested on data based on the situation in the Netherlands and compared based on computation time and solution quality. The results show that the solution approach that solves both levels separately performs better when considering minimizing the number of bases. However, the solution approach that solves both levels simultaneously performs better when considering minimizing the number of ambulances. In addition, with the latter solution approach it is easier to make a good trade-off between minimizing the number of bases and ambulances because it considers a weighted objective function. However, the computation time of this approach increases exponentially with the input size whereas the computation time of the approach that solves both levels separately follows a more linear trend.

[1]  Charles S. ReVelle,et al.  The Maximum Availability Location Problem , 1989, Transp. Sci..

[2]  K Kristina Sharypova,et al.  Coordination and Analysis of Barge Container Hinterland Networks , 2012 .

[3]  Richard L. Church,et al.  The maximal covering location problem , 1974 .

[4]  Ilan Vertinsky,et al.  A simulation-based methodology for optimization of ambulance service policies , 1973 .

[5]  Rji Rob Basten,et al.  An iterative method for the simultaneous optimization of repair decisions and spare parts stocks , 2009 .

[6]  RICHARD C. LARSON,et al.  A hypercube queuing model for facility location and redistricting in urban emergency services , 1974, Comput. Oper. Res..

[7]  Mark S. Daskin,et al.  Strategic facility location: A review , 1998, Eur. J. Oper. Res..

[8]  Geoffrey N. Berlin,et al.  Mathematical analysis of emergency ambulance location , 1974 .

[9]  C. Revelle,et al.  A Reliability-Constrained Siting Model with Local Estimates of Busy Fractions , 1988 .

[10]  Rji Rob Basten,et al.  Practical extensions to the level of repair analysis , 2010 .

[11]  Shane G. Henderson,et al.  Ambulance Service Planning: Simulation and Data Visualisation , 2005 .

[12]  Gilbert Laporte,et al.  Ambulance location and relocation models , 2000, Eur. J. Oper. Res..

[13]  Patrizia Beraldi,et al.  Designing robust emergency medical service via stochastic programming , 2004, Eur. J. Oper. Res..

[14]  Kommer Gj,et al.  Ambulances binnen bereik. Analyse van de spreiding enbeschikbaarheid van de ambulancezorg in Nederland , 2003 .

[15]  Gilbert Laporte,et al.  Solving an ambulance location model by tabu search , 1997 .

[16]  R. Church,et al.  The maximal covering location problem , 1974 .

[17]  S I Harewood,et al.  Emergency ambulance deployment in Barbados: a multi-objective approach , 2002, J. Oper. Res. Soc..

[18]  Hsing Kenneth Cheng,et al.  A Simulation Model for the Analysis and Management of An Emergency Service System , 1997 .

[19]  A. A. Aly,et al.  Probabilistic Formulation of the Emergency Service Location Problem , 1978, The Journal of the Operational Research Society.

[20]  Daniel Serra,et al.  Locating emergency services with different priorities: the priority queuing covering location problem , 2008, J. Oper. Res. Soc..

[21]  Charles S. ReVelle,et al.  The Location of Emergency Service Facilities , 1971, Oper. Res..

[22]  Jo van Nunen,et al.  Production , Manufacturing and Logistics Dynamic demand fulfillment in spare parts networks with multiple customer classes , 2013 .

[23]  Vladimir Marianov,et al.  Siting Emergency Services , 1995 .

[24]  Xiaoyan Zhu,et al.  Covering models and optimization techniques for emergency response facility location and planning: a review , 2011, Math. Methods Oper. Res..

[25]  Martijn Mes,et al.  A generalized simulation model of an integrated emergency post , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[26]  Zvi Drezner,et al.  Discrete cooperative covering problems , 2011, J. Oper. Res. Soc..

[27]  Mark S. Daskin,et al.  A Maximum Expected Covering Location Model: Formulation, Properties and Heuristic Solution , 1983 .

[28]  Kapil Kumar Gupta,et al.  Ambulance deployment analysis: A case study of Bangkok , 1987 .

[29]  Y. Sheffi,et al.  Relationship between freight accessibility and logistics employment in US counties , 2013 .

[30]  J. Goldberg,et al.  A simulation model for evaluating a set of emergency vehicle base locations: development, validation, and usage. , 1990, Socio-economic planning sciences.

[31]  Reinaldo Morabito,et al.  Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model , 2007, Comput. Oper. Res..

[32]  Tom Van Woensel,et al.  A Vehicle Routing Problem with Flexible Time Windows , 2014, Comput. Oper. Res..

[33]  Patrizia Beraldi,et al.  A probabilistic model applied to emergency service vehicle location , 2009, Eur. J. Oper. Res..

[34]  Jc Jan Fransoo,et al.  Ocean Container Transport: An Underestimated and Critical Link in Global Supply Chain Performance , 2010 .

[35]  Vladimir Marianov,et al.  The Queueing Maximal availability location problem: A model for the siting of emergency vehicles , 1996 .

[36]  Erwin W. Hans,et al.  Vehicle routing under time-dependent travel times: The impact of congestion avoidance , 2012, Comput. Oper. Res..

[37]  Nilay Noyan,et al.  Alternate risk measures for emergency medical service system design , 2010, Ann. Oper. Res..

[38]  Reinaldo Morabito,et al.  Towards unified formulations and extensions of two classical probabilistic location models , 2005, Comput. Oper. Res..

[39]  Alexander Skabardonis,et al.  A spatial queuing model for the emergency vehicle districting and location problem , 2009 .

[40]  Reinaldo Morabito,et al.  Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model , 2011 .

[41]  Esra Köktener Karasakal,et al.  A maximal covering location model in the presence of partial coverage , 2004, Comput. Oper. Res..

[42]  Reinaldo Morabito,et al.  A multiple dispatch and partial backup hypercube queuing model to analyze emergency medical systems on highways , 2007 .

[43]  Egon Lüftenegger,et al.  A Framework for Business Innovation Directions , 2011 .