  The container relocation problem is a combinatorial optimisation problem
aimed at finding a sequence of container relocations to retrieve all containers
in a predetermined order by minimising a given objective. Relocation rules
(RRs), which consist of a priority function and relocation scheme, are
heuristics commonly used for solving the mentioned problem due to their
flexibility and efficiency. Recently, in many real-world problems it is
becoming increasingly important to consider energy consumption. However, for
this variant no RRs exist and would need to be designed manually. One
possibility to circumvent this issue is by applying hyperheuristics to
automatically design new RRs. In this study we use genetic programming to
obtain priority functions used in RRs whose goal is to minimise energy
consumption. We compare the proposed approach with a genetic algorithm from the
literature used to design the priority function. The results obtained
demonstrate that the RRs designed by genetic programming achieve the best
performance.
