Citation

Hu H, He J, He X, Yang W, Nie J, Ran B. J. Traffic Transp. Eng. Engl. Ed. 2019; 6(5): 441-454.

Copyright

(Copyright © 2019, Periodical Offices of Chang'an University, Publisher Elsevier Publishing)

DOI

10.1016/j.jtte.2019.07.001

PMID

unavailable

Abstract

In the emergency management of disruptions, efficient emergency material scheduling (EMS) is a key factor to save people's lives and reduce loss. Based on the literature of EMS and related areas in recent years, the research was summarized from two aspects of EMS optimization model and algorithms. It is concluded that the EMS optimization models mainly aim at the shortest time, shortest distance, minimum cost, maximum satisfaction and fairness, etc. The constraints usually include the quantity of supply depots, relief supply and vehicles, the types of commodities, the road network conditions, the budgets and the demand forecast of emergency materials. Multi-objective model is more complex and it usually considers more than one objective. To find the optimized solution, the multi-objective model with complex constraints needs more efficient algorithms. The existing algorithms, including mathematic algorithm and heuristic algorithm, have been categorized. For NP-hard (non-deterministic polynomial hard) problems, heuristic algorithms should be designed, which mainly include genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), etc. Based on the characteristics of the optimization model and various algorithms, appropriate algorithm or tools should be chosen and designed to obtain the optimized solution of EMS model. Finally, the development trends of EMS optimization model and algorithm in the future are proposed.

Language: en

Keywords

Disruption; Emergency material scheduling (EMS); Heuristic algorithm; Optimization model