Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Petter Pilesjö

Petter Pilesjö

Professor

Petter Pilesjö

Multi-Objective Optimization Using Evolutionary Cuckoo Search Algorithm for Evacuation Planning

Författare

  • Tomé Sicuaio
  • Olive Niyomubyeyi
  • Andrey Shyndyapin
  • Petter Pilesjö
  • A Mansourian

Summary, in English

Proper emergency evacuation planning is a key to ensuring the safety and efficiency of resources allocation in disaster events. An efficient evacuation plan can save human lives and avoid other effects of disasters. To develop effective evacuation plans, this study proposed a multi-objective optimization model that assigns individuals to emergency shelters through safe evacuation routes during the available periods. The main objective of the proposed model is to minimize the total travel distance of individuals leaving evacuation zones to shelters, minimize the risk on evacuation routes and minimize the overload of shelters. The experimental results show that the Discrete Multi-Objective Cuckoo Search (DMOCS) has better and consistent performance as compared to the standard Multi-Objective Cuckoo Search (MOCS) in most cases in terms of execution time; however, the performance of MOCS is still within acceptable ranges. Metrics and measures such as hypervolume indicator, convergence evaluation and parameter tuning have been applied to evaluate the quality of Pareto front and the performance of the proposed algorithm. The results showed that the DMOCS has better performance than the standard MOCS.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap
  • Centrum för geografiska informationssystem (GIS-centrum)
  • Centrum för Mellanösternstudier (CMES)

Publiceringsår

2022-02-15

Språk

Engelska

Sidor

53-75

Publikation/Tidskrift/Serie

Geomatics

Volym

2

Issue

1

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Computer and Information Science
  • Physical Geography

Nyckelord

  • emergency evacuation planning
  • emergency evacuation planning; multi-objective optimization
  • MOCS algorithm
  • GIS
  • Operational research
  • Geospatial Artificial Intelligence (GeoAI)
  • Artificial Intelligence (AI)

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2673-7418