Authors:
Panwadee Tangpattanakul
1
and
Ilhem Quenel
2
Affiliations:
1
Capgemini Engineering, 4 avenue Didier Daurat, 31700 Blagnac, France
;
2
Capgemini Sophia Antipolis, 950 avenue de Roumanille, E. Golf-Park, Bâtiment TECK, 06410 Biot, France
Keyword(s):
Flying Taxi, Scheduling Problem, Metaheuristic, Genetic Algorithm, Simulated Annealing.
Abstract:
According to the traffic congestion problem in big cities around the world, some sustainable transportation technologies are researched and developed in these recent years. Flying taxi is a transportation mode, which is being developed from several major brands. It can become an alternative transportation mode in the future. In this work, a simplified optimization model of the flying taxi scheduling is proposed. Two algorithms, which consists of genetic algorithm and simulated annealing, are used to solve the problem. The experiments are conducted on 15 instances with different number of customer demands (between 10 and 200 demands) and different number of available flying taxis in the system (from 2 to 10 taxis). The experimental results show that both algorithms are efficient to solve the problem. The genetic algorithm obtains better quality solutions for the small and medium size instances but it spends more computation time than the simulated annealing. However, the simulated ann
ealing can solve the large instances and obtain good solutions in reasonable time.
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