Multi-objective genetic algorithms for flights amalgamation problem

Within the airline, any disturbance to normal operations has a dramatic impact, and usually imposes high additional costs. Because of irregular events during daily operations. When disruptions occur, flight schedules are affected due to the resulting infeasible flight schedule and improper assignments. Therefore, airlines need to recover disrupted schedule as soon as possible and minimize the extra cost as well as the impact on the airline image and customer satisfaction. Approaches such as linear programming, network modeling, greedy heuristics and decisions support systems are wellknown approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Genetic Algorithm. The aim of this research is to introduce the concept of Genetic Algorithm as a tool to solve irregular airline operation, amalgamation problem and monitor the reasons of schedule disruptions. The proposed model could obtain optimal solutions within seconds based on real data from medium airline case.