Diversity-Oriented Bi-Objective Hyper-heuristics for Patrol Scheduling
The patrol scheduling problem is concerned with assigning security teams to different stations for distinct time intervals while respecting a limited number of contractual constraints. The objective is to minimise the total distance travelled while maximising the coverage of the stations with respect to their security requirement levels. This paper introduces a hyper-heuristic strategy focusing on generating diverse solutions for a bi-objective patrol scheduling problem. While a variety of hyper-heuristics have been applied to a large suite of problem domains usually in the form of single-objective optimisation, we suggest an alternative approach for solving the patrol scheduling problem with two objectives. An adaptive weighted-sum method with a variety of weight schedules is used instead of a traditional static weighted-sum technique. The idea is to reach more diverse solutions for different objectives. The empirical analysis performed on the Singapore train network dataset demonstrate the effectiveness of our approach.
