Cost Minimization in 3D Bin Packing under Orientation and Operational Constraints: A Case Study in E-Commerce Fulfillment

Abstract

Inefficient parcel packing in e-commerce fulfillment causes excessive void space, inflated dimensional weight charges, and unnecessary dunnage costs. This issue is rightly classified as a three-dimensional bin packing problem (3D-BPP), which is NP-hard and computationally intractable at realistic scales. Current industry practice relies on manual, horizontal-only packing with predefined box sizes, thereby systematically overlooking opportunities to reduce costs through flexible orientation. While extensive literature addresses 3D-BPP, existing research typically applies operational constraints as post hoc checks after geometric optimization, and rarely combines discrete box selection with explicit logistics cost minimization. This study develops and evaluates an orientation-flexible packing framework that integrates fragility protection, weight precedence, and base-support stability into the heuristic placement process, rather than filtering out infeasible solutions after packing. The framework selects from a set of discrete, predefined box sizes and minimizes the total logistics cost, including packaging and dimensional weight charges. Three strategies—a horizontal-only baseline, First Fit Decreasing (FFD), and Best Fit (BF) with orientation flexibility, are systematically compared using simulation experiments on 600 real-world e-commerce orders from a personal care products fulfillment operation. Results demonstrate that BF achieves a 4.47% reduction in total logistics cost, 9.31% reduction in void space, and 9.31% reduction in dunnage cost relative to the baseline. At the same time, FFD is approximately eight times faster than BF, with moderate efficiency gains. Cross-validation confirms solution stability across heterogeneous subsets of orders, and sensitivity analyses verify robustness to variations in support thresholds, dimensional-weight pricing, and box-material costs. These findings provide actionable guidance for context-dependent strategy selection, demonstrating that integrating operational constraints into packing heuristics do not degrade cost performance and remain computationally feasible for real-world e-commerce fulfillment.