https://sunkanghong-wang.github.io/tags/packing/Recent content in Packing on Sunkanghong WangHugo -- 0.147.4enMon, 13 Oct 2025 00:00:00 +0000https://sunkanghong-wang.github.io/publications/circle-bin/Mon, 13 Oct 2025 00:00:00 +0000https://sunkanghong-wang.github.io/publications/circle-bin/<h5 id="abstract">Abstract</h5> <p>This study explores a specific variant of the classic two-dimensional bin-packing problem, known as the Circle Bin-Packing Problem with Rectangular Items (CBPP-RI). This problem involves the orthogonal packing of rectangular items into the fewest possible circular bins and has significant practical implications. We propose a novel and efficient Goal-Driven Iterated Local Search (GDILS) approach for solving CBPP-RI, which integrates a customized method that effectively addresses cold starts and prevents entrapment in local optima. To avoid unnecessary searches, we use lower bounds, which are improved by accounting for the inevitable waste produced by rectangular items at the edges of circular bins. To achieve good performance in single-bin packing, we propose a maximal-space-based heuristic, which introduces the widely used concept of maximal-space from other rectangle packing problems. The experimental results demonstrate that GDILS performs well and show that our method is not only applicable to CBPP-RI but also effective for other related packing problems. To establish a valid benchmark for future research, we also generate a new dataset for CBPP-RI and conduct extensive experiments.</p>https://sunkanghong-wang.github.io/publications/arcflow/Wed, 01 Jan 2025 00:00:00 +0000https://sunkanghong-wang.github.io/publications/arcflow/<h5 id="abstract">Abstract</h5> <p>This study introduces an arc-flow formulation and the first branch-and-price-and-cut (BPC) algorithm designed to solve the bin-packing problem with fragile objects (BPPFO). This variant of the bin-packing problem originates in the field of telecommunications, particularly in the allocation of cellular calls to frequency channels. The arc-flow formulation is inspired by previous studies and modifies the graph construction method to accommodate fragility constraints. We proved the correctness of this formulation and demonstrated its superiority in instances with small maximum fragility through extensive experiments. The proposed BPC algorithm leverages advanced cutting and packing techniques and incorporates innovative elements such as problem reduction, additional cutting planes, and a label-setting-based exact pricing algorithm. The experimental results demonstrate that the proposed BPC algorithm is highly competitive with the state-of-the-art algorithm for solving the BPPFO and can successfully solve several previously unsolved instances.</p>