Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm |
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Authors: | Tung-Kuan Liu Chi-Ruey Jeng Yu-Hern Chang |
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Institution: | 1. Department of Mechanical and Automation Engineering , National Kaohsiung First University of Science and Technology , Kaohsiung, Taiwan, R.O.C tkliu@ccms.nkfust.edu.tw;3. Department of Transportation and Communication Management Science , National Cheng-Kung University , Taiwan, R.O.C |
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Abstract: | Abstract This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations. |
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Keywords: | Disruption management multi-objective optimization genetic algorithm airline schedule recovery method of inequalities |
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