Packing Unequal Circles into a Square Container by Partitioning Narrow Action Spaces and Circle Items

Abstract: We address the NP-hard problem of finding a non-overlapping dense packing pattern for n Unequal Circle items in a two-dimensional Square Container (PUC-SC) such that the size of the container is minimized. Based on our previous work on an Action Space based Global Optimization (ASGO) that approximates each circle item as a square item to efficiently find the large unoccupied spaces, we propose an optimization algorithm based on the Partitioned Action Space and Partitioned Circle Items (PAS-PCI). The PAS is to partition the narrow action space on the long side to find two equal action spaces to fully utilize the unoccupied spaces. The PCI is to partition the circle items into four groups based on size for the basin hopping strategy. Experiments on two sets of benchmark instances show the effectiveness of the proposed method. In comparison with our previous algorithm ASGO on the 68 tested instances that ASGO published, PAS-PCI not only gains smaller containers in 64 instances and matches the other 4 but also runs faster in most instances. In comparison with the best record of the Packomania website on a total of 98 instances, PAS-PCI finds smaller containers on 82 and matches the other 16. Note that we updated 19 records for (47-48, 51-54, 57, 61-72) that had been kept unchanged since 2013.