Emergency Resource Allocation for Multi-Period Post-Disaster Using Multi-Objective Cellular Genetic Algorithm

Release time:2021-10-20

Impact Factor:3.367

DOI number:10.1109/ACCESS.2020.2991865

Journal:IEEE ACCESS

Abstract:As an important part of emergency response, the post-disaster emergency resource allocation is essential for mitigating disaster losses. To realize the effective allocation of relief materials and the reasonable selection of transportation routes, a multi-objective resource allocation model is proposed, considering the characteristics of uncertainty and persistence during rescue process. Furthermore, the multi-objective cellular genetic algorithm (MOCGA) is developed to solve the model by introducing the auxiliary population and neighborhood structure in the cellular automata. Finally, the comparison experiment proves that the overall performance of MOCGA is satisfactory compared with non-dominated multi-objective whale optimization algorithm (NSMOWOA), non-dominated multi-objective grey wolf optimizer (NSMOGWO) and non-dominated sorting genetic algorithm (NSGA-II) in the pareto front (PF), the hypervolume, the average value of objective function, and the PF ratio. Results show that MOCGA can solve the multi-objective dynamic emergency resource allocation model well, and can provide decision-makers with more excellent and diverse candidate rescue schemes than other algorithms. Besides, by analyzing the rescue schemes, this paper also provides a theoretical rescue scheme for decision-makers & x2019; scientific decisions.

First Author:Wang, FY; Pei, ZW; Dong, LJ ; Ma, J

Indexed by:Article

Discipline:Engineering

First-Level Discipline:Safety Science and Engineering

Document Type:J

Volume:8

Page Number:82255-82265

ISSN No.:2169-3536

Translation or Not:no

Date of Publication:2020-07-29

Included Journals:SCI