TY - GEN
T1 - A Meta-Heuristic Solution Approach to Isolated Evacuation Problems
AU - Krutein, Klaas Fiete
AU - Boyle, Linda Ng
AU - Goodchild, Anne
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper provides an approximation method for the optimization of isolated evacuation operations, modeled through the recently introduced Isolated Community Evacuation Problem (ICEP). This routing model optimizes the planning for evacuations of isolated areas, such as islands, mountain valleys, or locations cut off through hostile military action or other hazards that are not accessible by road and require evacuation by a coordinated set of special equipment. Due to its routing structure, the ICEP is NP-complete and does not scale well. The urgent need for decisions during emergencies requires evacuation models to be solved quickly. Therefore, this paper investigates solving this problem using a Biased Random-Key Genetic Algorithm. The paper presents a new decoder specific to the ICEP, that allows to translate in between an instance of the S-ICEP and the BRKGA. This method approximates the global optimum and is suitable for parallel processing. The method is validated through computational experiments.
AB - This paper provides an approximation method for the optimization of isolated evacuation operations, modeled through the recently introduced Isolated Community Evacuation Problem (ICEP). This routing model optimizes the planning for evacuations of isolated areas, such as islands, mountain valleys, or locations cut off through hostile military action or other hazards that are not accessible by road and require evacuation by a coordinated set of special equipment. Due to its routing structure, the ICEP is NP-complete and does not scale well. The urgent need for decisions during emergencies requires evacuation models to be solved quickly. Therefore, this paper investigates solving this problem using a Biased Random-Key Genetic Algorithm. The paper presents a new decoder specific to the ICEP, that allows to translate in between an instance of the S-ICEP and the BRKGA. This method approximates the global optimum and is suitable for parallel processing. The method is validated through computational experiments.
UR - http://www.scopus.com/inward/record.url?scp=85135761873&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135761873&partnerID=8YFLogxK
U2 - 10.1109/WSC57314.2022.10015470
DO - 10.1109/WSC57314.2022.10015470
M3 - Conference contribution
AN - SCOPUS:85135761873
T3 - Proceedings - Winter Simulation Conference
SP - 2002
EP - 2012
BT - Proceedings of the 2022 Winter Simulation Conference, WSC 2022
A2 - Feng, B.
A2 - Pedrielli, G.
A2 - Peng, Y.
A2 - Shashaani, S.
A2 - Song, E.
A2 - Corlu, C.G.
A2 - Lee, L.H.
A2 - Chew, E.P.
A2 - Roeder, T.
A2 - Lendermann, P.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Winter Simulation Conference, WSC 2022
Y2 - 11 December 2022 through 14 December 2022
ER -