Abstract

Crew pairing is the primary cost checkpoint in airline crew scheduling. Because the crew cost comes second after the fuel cost, a substantial cost saving can be gained from effective crew pairing. In this paper, the cockpit crew pairing problem (CCPP) of a budget airline was studied. Unlike the conventional CCPP that focuses solely on the cost component, many more objectives deemed to be no less important than cost minimisation were also taken into consideration. The adaptive non-dominated sorting differential algorithm III (ANSDE III) was proposed to optimise the CCPP against many objectives simultaneously. The performance of ANSDE III was compared against the NSGA III, MOEA/D, and MODE algorithms under several Pareto optimal measurements, where ANSDE III outperformed the others in every metric.

Highlights

  • Airline scheduling is one of the most challenging planning processes encountered by the airline industry

  • To signify the statistical property of some input parameters used in the contested algorithms, which are based on random number generators, all algorithms were run with three replicates

  • The values of the objectives obtained from the other algorithms compared with those from ANSDE III were derived from dividing the actual values of those algorithms by the actual values of ANSDE III

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Summary

Introduction

Airline scheduling is one of the most challenging planning processes encountered by the airline industry. Airline crew scheduling consists of the two sub-problems of crew pairing and crew rostering, which are normally solved successively The former determines the set of flight sequences with a minimum cost to encompass a predefined set of flight legs, as prescribed in the timetable of the airline for a given period while abiding by the diverse and complex legal restrictions enacted by the federation’s safety regulations and the company’s agreements. Under this context, a pairing means a crew itinerary or a tour of duty to be followed by a crew member. The optimised CCPP would bring about increasing cockpit crew utilisation and reducing wastage time due to other reasons apart from flights (Zeren & Özkol, 2016)

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