Bio-Inspired Meta-Heuristics for Emergency Transportation Problems

• Main Authors: Min-Xia Zhang, Bei Zhang, Yu-Jun Zheng
• Format: Article
• Language: English
• Published: MDPI AG 2014-02-01
• Series: Algorithms
• Subjects: bio-inspired algorithms; transportation problems; planning and scheduling; biogeography-based optimization (BBO)
• Online Access: http://www.mdpi.com/1999-4893/7/1/15

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.