Title: Hybrid tabu searches for effective airport gate management

Authors: Chun-Hung Cheng; Angappa Gunasekaran; Sin C. Ho; Chuek-Lam Kwan; Tobun Dorbin Ng

Addresses: Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, NT, Kowloon, Hong Kong ' School of Business and Public Administration, California State University, Bakersfield, 9001 Stockdale Highway, 20BDC/140, Bakersfield, CA 93311-1022, USA ' Department of Economics and Business, Aarhus University, Fuglesangs Allé, Building 2628, Room 320, 8210 Aarhus V, Denmark ' OOCL, 5/Fl., Lakeside 2, 10 Science Park West Avenue, Hong Kong Science Park, Shatin, NT, Kowloon, Hong Kong ' Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, NT, Kowloon, Hong Kong

Abstract: In this research, we are concerned with assigning gates of an airport to arriving and departing aircrafts. This is referred to as the gate assignment problem (GAP). This is an important planning problem, as improper assignment may result in flight delays and inefficient use of airport resources. As solving this problem to optimality is ineffective for many realistic situations, we examine the use of a meta-heuristic. Specifically, we attempt to use tabu search (TS). Although the application of TS in GAP is not new, we explore to introduce path relinking (PR) to improve the performance of TS. In our computation, we find that the PR feature produces desirable results. Further, the experiment using flight data from Incheon International Airport of Korea (ICN) shows that TS+PR performs well when compared with meta-heuristics such as genetic search (GS), simulated annealing (SA), a pure tabu search (TS), and a hybrid of SA and TS.

Keywords: airport gate assignment; meta-heuristics; path relinking; simulated annealing; genetic search; performance; tabu search.

DOI: 10.1504/IJOR.2017.087827

International Journal of Operational Research, 2017 Vol.30 No.4, pp.484 - 522

Available online: 13 Oct 2017

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