A tutorial on hypercube queueing models and some practical applications in Emergency Service Systems

This paper presents some extensions and applications of hypercube queueing models todescribe server-to-customer type Emergency Service Systems. The classical hypercube is a well-known spatially distributed queueing model effective in analyzing these systems, based on Markovian analysis approximations. Experience has shown that each real life Emergency Service System may have its own unique characteristics so that each system may require a particular hypercube queueing model incorporating those characteristics. Some of these distinctive characteristics are considered in the extensions presented in this tutorial such as dispatch policy based on random selection of the server to take an incoming call; partial cooperation among servers whereby depending on where the call is coming from, some servers cannot take the call; servers with additional workload coming from walk-in nonemergency customers such as in customer-to-server systems; existence of calls requiring the dispatch of more than one server; existence of more than one type of servers in the system, for instance paramedical and medical units in emergency medical systems. In this study, we present a set of these models based on the smallest non-trivial service systems. For each model, the construction of the system of equations for equilibrium hypercube state probabilities and the evaluation of particular operational characteristics are described.

[1]  Reinaldo Morabito,et al.  A note on solutions to the maximal expected covering location problem , 2003, Comput. Oper. Res..

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

[3]  Vladimir Marianov,et al.  Location–Allocation of Multiple-Server Service Centers with Constrained Queues or Waiting Times , 2002, Ann. Oper. Res..

[4]  Kenneth Chelst,et al.  Multiple Unit Dispatches in Emergency Services: Models to Estimate System Performance , 1981 .

[5]  Richard Larson,et al.  O.R. Models for Homeland Security , 2004 .

[6]  Charles ReVelle,et al.  Review, extension and prediction in emergency service siting models , 1989 .

[7]  Deise Maria Bertholdi Costa Uma metodologia iterativa para determinação de zonas de atendimento de serviços emergenciais , 2003 .

[8]  Roberto D. Galvão,et al.  Solução do problema de localização de máxima disponibolidade utilizando o modelo hipercubo , 2003 .

[9]  J. P. Jarvis,et al.  Approximating the Equilibrium Behavior of Multi-Server Loss Systems , 1985 .

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

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

[12]  N. Yu. Kuznetsov,et al.  Heuristic methods for the analysis of a queuing system describing emergency medical service deployed along a highway , 2006 .

[13]  Reinaldo Morabito,et al.  Emergency service systems: The use of the hypercube queueing model in the solution of probabilistic location problems , 2008, Int. Trans. Oper. Res..

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

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

[16]  Reinaldo Morabito,et al.  Non-homogeneous servers in emergency medical systems: Practical applications using the hypercube queueing model , 2008 .

[17]  Reinaldo Morabito,et al.  MODELO HIPERCUBO: ANÁLISE E RESULTADOS PARA O CASO DE SERVIDORES NÃO-HOMOGÊNEOS , 2001 .

[18]  Reinaldo Morabito,et al.  Analysing emergency medical service ambulance deployment on a Brazilian highway using the hypercube model , 2001, J. Oper. Res. Soc..

[19]  Richard C. Larson,et al.  Urban Operations Research , 1981 .

[20]  Cem Saydam,et al.  A multiperiod set covering location model for dynamic redeployment of ambulances , 2008, Comput. Oper. Res..

[21]  Cem Saydam,et al.  Accurate estimation of expected coverage: revisited , 2003 .

[22]  Igor N. Kovalenko,et al.  A hypercube queueing loss model with customer-dependent service rates , 2008, Eur. J. Oper. Res..

[23]  Vladimir Marianov,et al.  Optimal location of multi-server congestible facilities operating as M/Er/m/N queues , 2009, J. Oper. Res. Soc..

[24]  Rajan Batta,et al.  The Maximal Expected Covering Location Problem: Revisited , 1989, Transp. Sci..

[25]  Jonathan Halpern The Accuracy of Estimates for the Performance Criteria in Certain Emergency Service Queueing Systems , 1977 .

[26]  Horst A. Eiselt,et al.  Location analysis: A synthesis and survey , 2005, Eur. J. Oper. Res..

[27]  Roberto D. Galvão,et al.  O uso do modelo hipercubo na solução de problemas de localização probabilísticos , 2000 .

[28]  Richard C. Larson,et al.  Police Patrol-Initiated Activities Within a Systems Queueing Model , 1982 .

[29]  Reinaldo Morabito,et al.  A hypercube queueing model embedded into a genetic algorithm for ambulance deployment on highways , 2007, Ann. Oper. Res..

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

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

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

[33]  James P. Jarvis,et al.  Modeling co-located servers and dispatch ties in the hypercube model , 1993, Comput. Oper. Res..

[34]  Nikolas Geroliminis,et al.  A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network , 2011, Eur. J. Oper. Res..

[35]  Reinaldo Morabito,et al.  An optimization approach for ambulance location and the districting of the response segments on highways , 2009, Eur. J. Oper. Res..

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