On Solving the Oriented Two-Dimensional Bin Packing Problem under Free Guillotine Cutting: Exploiting the Power of Probabilistic Solution Construction
This work addresses a combinatorial optimization problem relevant to industries like transportation and material cutting, but it is incremental as it builds on existing heuristics.
The authors tackled the oriented two-dimensional bin packing problem under free guillotine cutting by proposing a randomized multi-start heuristic and an evolutionary algorithm, with the evolutionary algorithm finding optimal solutions for 4 previously unsolved instances.
Two-dimensional bin packing problems are highly relevant combinatorial optimization problems. They find a large number of applications, for example, in the context of transportation or warehousing, and for the cutting of different materials such as glass, wood or metal. In this work we deal with the oriented two-dimensional bin packing problem under free guillotine cutting. In this specific problem a set of oriented rectangular items is given which must be packed into a minimum number of bins of equal size. The first algorithm proposed in this work is a randomized multi-start version of a constructive one-pass heuristic from the literature. Additionally we propose the use of this randomized one-pass heuristic within an evolutionary algorithm. The results of the two proposed algorithms are compared to the best approaches from the literature. In particular the evolutionary algorithm compares very favorably to current state-of-the-art approaches. The optimal solution for 4 previously unsolved instances could be found.