Solving Aircraft Landing Problem Using Constraint Handling Technique And Population Based Algorithms

This thesis addresses the problem of sequencing aircraft landings at an airport. This problem is known as Aircraft Landing Scheduling (ALS). ALS is a part of Aircraft Landing Problem (ALP). Given a set of aircrafts and runways, the objective is to minimise the total deviation from the target landing time for each aircraft. There are costs associated with landing either earlier or later than a target landing time for each aircraft. Each aircraft must land on one of the runways within its predetermined time windows such that separation criteria between all pairs of planes are satisfied. This thesis is an attempt to propose a solution that use constraint handling technique and population-based algorithm to optimise ALS. We apply ALS as mixed-integer problem with side constraints of time window for each aircraft. The algorithms are used to generate a population of random agents (solutions) which represent the aircraft landing sequence. To deal with the constraints, a constraint handling technique is applied. The constraint handling technique is adapted to reduce the minimum violation by relaxing the linear constraint into unconstrained form. The proposed solution is implemented and tested on the public data from OR Library involving up to 50 aircraft and 1 runway. The computational results show that the algorithm can solve the problem optimally