Open AccessComparison of two hybrid algorithms on incorporated aircraft routing and crew pairing problems
Author(s) -
Najihah Mohamed,
Nurul Akmal Mohamed,
Nurul Huda Mohamed,
N Subani
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v18.i3.pp1665-1672
Subject(s) - crew , pairing , routing (electronic design automation) , particle swarm optimization , integer programming , computer science , mathematical optimization , genetic algorithm , integer (computer science) , set (abstract data type) , algorithm , operations research , engineering , mathematics , aeronautics , computer network , physics , superconductivity , quantum mechanics , programming language
In airline operations planning, a sequential method is traditionally used in airline system. In airline systems, minimizing the costs is important as they want to get the highest profits. The aircraft routing problem is solved first, and then pursued by crew pairing problem. The solutions are suboptimal in some cases, so we incorporate aircraft routing and crew pairing problems into one mathematical model to get an exact solution. Before we solve the integrated aircraft routing and crew pairing problem, we need to get the aircraft routes (AR) and crew pairs (CP). In this study, we suggested using genetic algorithm (GA) to develop a set of AR and CP. By using the generated AR and CP, we tackle the integrated aircraft and crew pairing problems using two suggested techniques, Integer Linear Programming (ILP) and Particle Swarm Optimization (PSO). Computational results show that GA's executed of AR and CP and then solved by ILP obtained the greatest results among all the methods suggested.