Track: Sustainability in Operations and Supply Chain

Abstract

Airports as major transportation hubs need to transport a large number of travelers every day. Effectively managing such a large transportation system without compromising safety has always been a huge challenge. One of the keys to enhancing overall airport management is improving operational efficiency, which includes optimizing the allocation and schedules of limited resources, such as workforce and equipment. This paper proposed a method for generating optimal job schedules for Ground Service Equipment and Ground Support Staff using a two-dimensional genetic algorithm and validating using discrete-event simulations. For the 2D-GA, the method for selecting the parents is the truncation based on a preset threshold, for crossover is both the horizontal and vertical swap by generating random exchange points, and for mutation is the random resetting. The iteration for generating new offspring, or new solutions, will stop once the stop condition is met which means the optimal solution(s) is found. This paper also presents the optimization of job scheduling using the two-dimensional genetic algorithm using real flight schedules from an airport. The schedule is generated in MATLAB and used as input to the Simio simulation model for validation.