A multi-agent genetic algorithm based on natural coding for emergency resources scheduling problems

Unexpected accidents, such as earthquakes, snowstorms, and tsunamis, occur frequently at present. Emergency management is an important subject in both management science and social science, and has attracted increasing attentions. It is very important to determine emergency resources scheduling quic...

Full description

Saved in:
Bibliographic Details
Published in2016 IEEE Congress on Evolutionary Computation (CEC) pp. 2706 - 2711
Main Authors Haolong Wu, Jing Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2016
Subjects
Algorithm design and analysis
Emergency management
Genetic algorithms
Lattices
Logistics
Multi-agent genetic algorithm
Scheduling
Sociology
Statistics
Online AccessGet full text

Cover

More Information
Summary:Unexpected accidents, such as earthquakes, snowstorms, and tsunamis, occur frequently at present. Emergency management is an important subject in both management science and social science, and has attracted increasing attentions. It is very important to determine emergency resources scheduling quickly and efficiently from multiple emergency logistics centers, as supply points, to multiple disaster affected points. In order to improve the efficiency of supplying organization and reduce casualties and economic losses, a decision support model whose target is to minimize the earliest rescuing time, the latest rescuing time and the number of supply activities simultaneously is first designed. Then, a multiagent genetic algorithm using natural coding is proposed to solve the designed problem. Computational experiments show that the proposed model is reasonable and the proposed algorithm is valid. At the same time, the scheduling found by the proposed algorithm can help decision-makers make a rational decision.
DOI:10.1109/CEC.2016.7744129