Decision Support System to Solve Single-Container Loading Problem Considering Practical Constraints

Natalia Romero-Olarte, Santiago Amézquita-Ortiz, John Willmer Escobar and David Álvarez-Martínez ()
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Natalia Romero-Olarte: Department of Industrial Engineering, Universidad de los Andes, Bogotá 111711, Colombia
Santiago Amézquita-Ortiz: Department of Industrial Engineering, Universidad de los Andes, Bogotá 111711, Colombia
John Willmer Escobar: Department of Accounting and Finance, Universidad del Valle, Cali 760032, Colombia
David Álvarez-Martínez: Department of Industrial Engineering, Universidad de los Andes, Bogotá 111711, Colombia

Mathematics, 2025, vol. 13, issue 10, 1-22

Abstract: The container loading problem (CLP) has a broad spectrum of applications in industry and has been studied for over 60 years due to its high complexity. This paper addresses a realistic single-container loading scenario with practical constraints, including orientation limitations, maximum stacking weight, static stability, overall container weight limit, and fractional loading for multiple drop-off points (multidrop). We propose an open-source decision support system (DSS) implemented on a widely used platform (MS Excel®), which employs a heuristic algorithm to find efficient loading solutions under these constraints. The DSS uses a multi-start randomized constructive algorithm based on a maximal residual space representation. The constructive phase builds the loading pattern in vertical layers (columns or walls), while respecting all practical constraints. The performance of the proposed heuristic is validated through extensive computational experiments on classical benchmark instances, comparing its results against the recent state-of-the-art methods. We also analyze the impact of multi-drop constraints on utilization metrics. The DSS features an interactive interface for creating/loading instances, visualizing step-by-step packing patterns, and displaying key statistics, thus providing a user-friendly decision tool for practitioners.

Keywords: container loading problem; decision support system; heuristics; multi-drop loading; packing; stability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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