Bio-Inspired Meta-Heuristics for Emergency Transportation Problems

Algorithms

Min-Xia Zhang¹  Bei Zhang¹ 

[1] College of Information Engineering, Zhejiang University of Technology, 288 Liuhe Road, Hangzhou 310023, China

关键词: bio-inspired algorithms;    transportation problems;    planning and scheduling;    biogeography-based optimization (BBO);   

DOI  :  10.3390/a7010015

来源: mdpi

【 摘 要 】

Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), etc., for solving emergency transportation problems. We then propose a new hybrid biogeography-based optimization (BBO) algorithm, which outperforms some state-of-the-art heuristics on a typical transportation planning problem.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.