A Heuristics Algorithm for Centralized Deicing Scheduling Problem

DOI

10.2991/msbda-19.2019.33How to use a DOI?

Keywords

Deicing, Delay, Optimize, Scheduling, Simulation

Abstract

For the solution of the deicing delay, the greedy randomized adaptive search procedure (GRASP) was applied to optimize the scheduling scheme. Based on the simulation software, the departure data of an international airport was used to verify the validity of the proposed algorithm and compare the simulation results with the first-come, first-served (FCFS), greedy without availability check (GWOAC), and greedy with availability check (GWAC). In the model, the cost of the deicing time window, the deicing queue time and the moving distances of aircraft were included in the objective function. The simulation experiments on 283 instances results show that GRASP outperforms other algorithms on aircraft deicing queue time and take-off delay time. Furthermore, in order to obtain an optimal scheduling scheme, vehicles’ workload is balanced by adjusting the model after evaluating the working hours of each deicing vehicle.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiaqi Shen
AU  - Peng Yang
AU  - Hongwei Wang
AU  - Yiming Cao
PY  - 2019/08
DA  - 2019/08
TI  - A Heuristics Algorithm for Centralized Deicing Scheduling Problem
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
PB  - Atlantis Press
SP  - 210
EP  - 216
SN  - 2352-538X
UR  - https://doi.org/10.2991/msbda-19.2019.33
DO  - 10.2991/msbda-19.2019.33
ID  - Shen2019/08
ER  -