Title: Biogeography-based optimisation for road recovery problem considering value of delay after urban waterlog disaster

Authors: Lingpeng Meng; Qi Kang; Chuanfeng Han; Shaolong Hu

Addresses: School of Electronics and Information Engineering, Institute of Urban Construction and Emergency Management, Tongji University, Shanghai, China ' School of Electronics and Information Engineering, Tongji University, Shanghai, China ' School of Economics and Management, Institute of Urban Construction and Emergency Management, Tongji University, Shanghai, China ' School of Economics and Management, Institute of Urban Construction and Emergency Management, Tongji University, Shanghai, China

Abstract: An urban waterlog disaster (UWD) is caused by a rainfall when the urban drainage system fails to drain off the water produced by the rainfall. To reduce the influence of the waterlog disaster on society, a road recovery planning approach is developed that performs water volume estimation, and pumps collection, assignment, and transportation after a waterlog disaster. A mixed-integer programming model that considers value of delay to travellers was formulated. A biogeography-based optimisation (BBO) algorithm was presented to solve the problem. A real-world example of waterlog (caused by torrential rain on August 12, 2011, in the Pudong district of Shanghai, China) was presented using numerical analysis. The proposed approach emerges as a decision-making tool to help decision makers evaluate diverse recovery strategies before an UWD occurs, with the aim of optimising trade-off between economic costs and value of delay.

Keywords: urban waterlog disaster; emergency logistics; road recovery; mixed-integer programming; intelligent algorithm; biogeography-based optimisation; value of delay; transportation.

DOI: 10.1504/IJBIC.2017.083723

International Journal of Bio-Inspired Computation, 2017 Vol.9 No.3, pp.157 - 164

Received: 09 Feb 2017
Accepted: 26 Feb 2017

Published online: 07 Apr 2017 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article