  The container relocation problem is a challenging combinatorial optimisation
problem tasked with finding a sequence of container relocations required to
retrieve all containers by a given order. Due to the complexity of this
problem, heuristic methods are often applied to obtain acceptable solutions in
a small amount of time. These include relocation rules (RRs) that determine the
relocation moves that need to be performed to efficiently retrieve the next
container based on certain yard properties. Such rules are often designed
manually by domain experts, which is a time-consuming and challenging task.
This paper investigates the application of genetic programming (GP) to design
effective RRs automatically. The experimental results show that GP evolved RRs
outperform several existing manually designed RRs. Additional analyses of the
proposed approach demonstrate that the evolved rules generalise well across a
wide range of unseen problems and that their performance can be further
enhanced. Therefore, the proposed method presents a viable alternative to
existing manually designed RRs and opens a new research direction in the area
of container relocation problems.
