A goal-driven ruin and recreate heuristic for the 2D variable-sized bin packing problem with guillotine constraints

TL;DR

This paper introduces a novel goal-driven ruin and recreate heuristic for the 2D variable-sized bin packing problem with guillotine constraints, improving solution quality over existing methods across multiple variants.

Contribution

It presents a new heuristic combining ruin and recreate strategies with goal-driven techniques for the first time in this context.

Findings

Outperforms state-of-the-art algorithms on benchmark instances.

Effective for variants with item rotation and heterogeneous bins.

Achieves better bin utilization and reduced total bin area.

Abstract

This paper addresses the two-dimensional bin packing problem with guillotine constraints. The problem requires a set of rectangular items to be cut from larger rectangles, known as bins, while only making use of edge-to-edge (guillotine) cuts. The goal is to minimize the total bin area needed to cut all required items. This paper also addresses variants of the problem which permit 90{\deg} rotation of items and/or a heterogeneous set of bins. A novel heuristic is introduced which is based on the ruin and recreate paradigm combined with a goal-driven approach. When applying the proposed heuristic to benchmark instances from the literature, it outperforms the current state-of-the-art algorithms in terms of solution quality for all variants of the problem considered.