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A genetic algorithm for optimizing space utilization in aircraft hangar shop
Author(s) -
Li Xin,
Wang Z.X.,
Chan Felix T.S.,
Chung S.H.
Publication year - 2019
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12642
Subject(s) - genetic algorithm , service (business) , space (punctuation) , aeronautics , aerospace engineering , computer science , air space , operations research , engineering , economy , machine learning , economics , operating system
Abstract This study considers the aircraft placement problem in aircraft hangar shops (AHS) encountered by aircraft service companies. AHSs usually have irregular shapes, and aircraft, too, have special shapes. Moreover, frequent operations involving moving aircraft in and out are complicated. For these reasons, aircraft placement is difficult. The present study deals with operations management in AHS to optimize space utilization by placing a greater number of aircraft, which would greatly benefit aircraft services companies. Herein, a novel genetic algorithm (GA) based approach is applied to optimize space utilization. To exactly express the problem, practical and operational principles, including both in AHS and in outdoor areas, are abstracted based on interviews with the staff of an aircraft service company. Then, the placement space is modeled in an x – y coordinate system. In addition, a two‐dimensional geometry model for aircraft, consisting of seven parameters, is developed. Based on these works, a novel GA for solving the aircraft placement problem is developed. Finally, a practical instance with eight aircraft serviced by a company is tested. All eight aircraft are placed well by using the proposed approach. Compared to the previous scenario, where at most seven aircraft could be placed well, the proposed approach will greatly benefit aircraft service companies.