Citation

Zhang HG, Liang ZH, Liu HJ, Wang R, Liu YA. Data Brief 2020; 31: e105686.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.dib.2020.105686

PMID

unavailable

Abstract

This paper introduces a benchmark dataset to the research article entitled "Ensemble framework by using nature inspired algorithms for the early-stage forest fire rescue - a case study of dynamic optimization problems", by Zhang et al. [7]. Rescue ensemble that consists of rescue simulator and rescue algorithm is characterized by supporting the dynamic simulation of forest fire rescue. The purpose of rescue algorithm is to minimize the longest flight time of aircraft group II and the newly-increased burnt forest cost in one period, simultaneously. The map information in our dataset is from Google map and relevant parameters are also from the actual situation data. The benchmark contains 10 different maps that researchers can use to evaluate their own algorithms and compare their performance with our algorithm.

Language: en

Keywords

Dynamic optimization problem; Forest fire rescue; Forest fire suppression; Rescue ensemble; Rescue simulator; Unmanned platforms