Adaptive simulated annealing with greedy search for the circle bin packing problem

We introduce a new bin packing problem, termed the circle problem with circular items (CBPP-CI). The involves all into multiple identical bins as compact possible objective of minimizing number used bins. first define tangent occupying action (TOA) and propose constructive greedy algorithm that sequentially packs places to packed or boundaries. Moreover, avoid falling local minimum trap efficiently judge whether an optimal solution has been established, we continue present adaptive simulated annealing search (ASA-GS) explores exploits space efficiently. Specifically, offer two novel perturbation strategies jump out optimum incorporate achieve faster convergence. parameters ASA-GS are according so they can be size-agnostic across scale. design sets benchmark instances, empirical results show completely outperforms algorithm. for unequal circles fixed size container maximize area packed, advanced formulation (FSS) in terms quality computational cost, inferring our approach is not only adapted CBPP-CI but also works well when reduced one become typical problem.