Scheduling for airport baggage transport vehicles based on diversity enhancement genetic algorithm

Abstract

The scheduling problems for airport baggage transport vehicles are much influential to the quality of airport service. An optimal scheduling is very helpful to provide an efficient and safe airport operation and improve customers’ experience. To address the issue, in this paper, a novel genetic algorithm (GA) is proposed for the vehicles scheduling. To enhance the exploitation ability of GA, the algorithm is improved by considering both population diversity and population fitness simultaneously. In the proposed GA, a cooperative mechanism is employed to design the selection operation for genetic algorithm where both exploitation ability and exploration ability can be considered. Numerical experiments are conducted on widely used benchmarks, and several peer meta-heuristic algorithms are also used in performance comparison. To address the airport baggage transport vehicle scheduling problem, real data is adopted in the proposed algorithm for simulation. According to simulation results, the proposed algorithm is feasible and effective to obtain competitive performance and the airport baggage transport vehicles scheduling problem in is well addressed.