EURO 2025 Leeds
Abstract Submission

3155. Optimising Garment Remanufacturing: A Novel Approach to Two-Dimensional Irregular Multi-Bin Packing with Non-Fragmentation Constraints

Invited abstract in session MB-21: 2D Cutting and Packing, stream Cutting and packing (ESICUP).

Monday, 10:30-12:00
Room: Esther Simpson 2.12

Authors (first author is the speaker)

1. Nesma ElShishtawy
Analytics, Technology and Operations Department, University of Leeds
2. Julia Bennell
Leeds University Business School, University of Leeds
3. Pammi Sinha
School of Design , University of Leeds

Abstract

This study introduces a new variant of the cutting and packing problem: the Two-Dimensional Irregular Multi-Bin Packing with Non-Fragmentation Constraints (2D-IMBP-NFC). Motivated by upcycling and material reuse, the problem involves allocating and packing full garment clusters, non-fragmentable complete sets of pattern pieces, into irregularly shaped bins derived from disassembled deadstock garments. The methodology is structured into two integrated sub-problems: (i) a Piece and Bin Selection Sub-problem, solved using a linear programming (LP) model to allocate cluster instances across multiple irregular bins and a fallback fabric strip, subject to capacity and demand constraints; and (ii) a Placement Sub-problem, where a geometry-informed heuristic generates the initial layout by leveraging the spatial characteristics of both bins and garment clusters to guide feasible placements. A column-wise post-optimisation phase refines layout compaction for each bin, then selectively reassigns clusters initially allocated to the fabric strip into the freed bin space. Evaluated on real-world garment data, the proposed integration of mathematical optimisation with domain-specific heuristics, demonstrates significant potential for reducing the reliance on virgin material in garment manufacturing. Additionally, it offers a robust framework that addresses key operational constraints integral to advancing garment remanufacturing in the fashion industry.

Keywords

Status: accepted

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