Automated design of relocation rules for the dynamic container relocation problem

The container relocation problem (CRP) is an important combinatorial optimisation problem frequently encountered in container ports. To date, most studies have focused on the static variant of the problem, in which containers are solely retrieved from the yard. In contrast, real-world problems often involve containers arriving and being retrieved simultaneously, a scenario referred to as the dynamic CRP. Solving this dynamic variant using traditional optimisation methods can be challenging, as information about container arrivals is typically not known in advance. As a result, simple constructive heuristics, known as relocation rules (RRs), represent a better alternative for addressing this problem. However, RRs are highly domain specific, making the manual design of effective rules difficult. Therefore, this study employs genetic programming (GP) to generate new RRs tailored to the dynamic CRP automatically. To evaluate their performance, these automatically generated RRs are compared with several manually designed RRs across a wide range of dynamic problem scenarios. The results show that automatically generated RRs significantly outperform their manually designed counterparts, demonstrating the effectiveness of the proposed approach.