Scheduling ambulance crews for maximum coverage

This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for this subproblem. Two integer programming models that use the output of the tabu search algorithm are constructed for the main problem. Computational experiments with real data are conducted. A comparison of the results of the models is presented.

[1]  Arthur J. Swersey.  Chapter 6 The deployment of police, fire, and emergency medical units , 1994, Operations research and the public sector.

[2]  Ger Koole,et al.  Optimal Shift Scheduling with a Global Service Level Constraint , 2003 .

[3]  Said Salhi,et al.  Facility Location: A Survey of Applications and Methods , 1996 .

[4]  Tony Hürlimann,et al.  Modeling Framework , 2021, Hybrid Feedback Control.

[5]  Andreas T. Ernst,et al.  Staff scheduling and rostering: A review of applications, methods and models , 2004, Eur. J. Oper. Res..

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

[7]  J. Goldberg.  Operations Research Models for the Deployment of Emergency Services Vehicles , 2004 .

[8]  Erhan Erkut,et al.  Computational Comparison of Five Maximal Covering Models for Locating Ambulances , 2009 .

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

[10]  Maged Dessouky,et al.  A modeling framework for facility location of medical services for large-scale emergencies , 2007 .

[11]  Avijit Ghosh,et al.  Spatial analysis and location-allocation models , 1987 .

[12]  Erhan Erkut,et al.  Optimal ambulance location with random delays and travel times , 2008, Health care management science.

[13]  C. Saydam,et al.  Applications and Implementation A SEPARABLE PROGRAMMING APPROACH TO EXPECTED COVERAGE: AN APPLICATION TO AMBULANCE LOCATION , 1985 .

[14]  Jeffrey Goldberg,et al.  Locating Emergency Vehicle Bases When Service Time Depends on Call Location , 1991, Transp. Sci..

[15]  Richard C. Larson,et al.  Approximating the Performance of Urban Emergency Service Systems , 1975, Oper. Res..

[16]  Erhan Erkut,et al.  Technical Note - Approximating Vehicle Dispatch Probabilities for Emergency Service Systems with Location-Specific Service Times and Multiple Units per Location , 2009, Oper. Res..

[17]  Peter J. Kolesar,et al.  Improving the Sipp Approach for Staffing Service Systems That Have Cyclic Demands , 2001, Oper. Res..

[18]  Mark S. Daskin,et al.  LOCATION, DISPATCHING AND ROUTING MODELS FOR EMERGENCY SERVICES WITH STOCHASTIC TRAVEL TIMES , 1984 .

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

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

[21]  Gary M. Thompson.  Labor Staffing and Scheduling Models for Controlling Service Levels , 1997 .