The emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the different actors involved in emergencies management, neither scientific nor in industrial field, have developed intelligent tools to support the decisions in these particular contexts. This work, realized inside an Italian financed project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination, using a limited number of capacitated vehicles respecting a time limit. This problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Ants Colony Optimization algorithm (ACOa). Results and tests are given in order to validate the proposed model and to offer a solution for a real case treaty into the abovementioned project.

An orienteering-based approach to manage emergency situation

Carotenuto P;
2017

Abstract

The emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the different actors involved in emergencies management, neither scientific nor in industrial field, have developed intelligent tools to support the decisions in these particular contexts. This work, realized inside an Italian financed project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination, using a limited number of capacitated vehicles respecting a time limit. This problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Ants Colony Optimization algorithm (ACOa). Results and tests are given in order to validate the proposed model and to offer a solution for a real case treaty into the abovementioned project.
2017
Istituto Applicazioni del Calcolo ''Mauro Picone''
Inglese
Hilmi Berk Celikoglu, Abdullah Hilmi Lav, Mehmet Ali Silgu
"19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 September 2016, Istanbul, Turkey"
"19th EURO Working Group on Transportation Meeting" - EWGT2016
22
297
304
http://www.scopus.com/record/display.url?eid=2-s2.0-85019496316&origin=inward
elsevier B.V.
Amsterdam
PAESI BASSI
Sì, ma tipo non specificato
05/09/2016, 07/09/2016
Istanbul, Turkey
Routing; Orienteering; Metaheuristic; Ant Colony Optimization; Emergency
3
none
Baffo, I; Carotenuto, P; Rondine, S
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/335909
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