Pareto set as a model for dispatching resources in emergency Centres

  • Ricardo Guedes
  • Vasco FurtadoEmail author
  • Tarcísio Pequeno
  • Joel J. P. C. Rodrigues


The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. Understanding which are the best policies of dispatching as well as workload balancing are very important in the context FOG computing, which aims to distribute in part workload and services on fog devices (such as hardened routers, switches, IP video cameras, etc.). Fog-computing systems produce an ever-increasing service request impacting, for instance, to the power consumption on cloud servers. On the other hand, it is equally crucial to guarantee the quality of service (e.g., latency requirements) of end users. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.


Agent-based simulation Evolutionary algorithms Multi-objective optimization Dispatch centre 



This work has been partially supported by National Funding from the FCT - Fundação para a Ciência e a Tecnologia through the UID/EEA/50008/2013 Project; by Finep, with resources from Funttel, Grant No. 01.14.0231.00, under the Centro de Referência em Radiocomunicações - CRR project of the Instituto Nacional de Telecomunicações (Inatel), Brazil; by Brazilian National Council for Research and Development (CNPq) via Grant No. 309335/2017-5.

Compliance with ethical standards

Conflict of interest

No author has a conflict of interest with the contents of this manuscript.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of Fortaleza (UNIFOR)FortalezaBrazil
  2. 2.National Institute of Telecommunications (Inatel)Santa Rita do SapucaíBrazil
  3. 3.Instituto de TelecomunicaçõesLisbonPortugal

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