An adaptive lexicographic MILP approach for cut order planning

Abstract Cut order planning is one of the most important optimization problems in the apparel industry. As an NP‐hard problem, manual techniques usually lead to fabric waste, while existing models tend to remain detached from operational realities. This research develops a lexicographic mixed‐integer linear programming model to address these challenges. The model applies a hierarchical objective formulation sequentially targeting (i) minimization of fabric consumption, (ii) reduction of operational complexity, and (iii) improvement of order fulfillment reliability. An important goal is to bridge the gap between theoretical optimization and industrial practice. The proposed framework constructs cut plans over an existing marker database, while a complementary heuristic adaptively expands that database. Validated against industrial instances, the system demonstrated measurable improvement in fabric savings and greater planning reliability. This research establishes a powerful and practical decision‐support tool matching theory with industrial applicability.