2982. Integrating GRASP and Beam Search for the Container Loading Problem Under Practical Constraints
Invited abstract in session MA-21: Packing with practical constraints, stream Cutting and packing (ESICUP).
Monday, 8:30-10:00Room: Esther Simpson 2.12
Authors (first author is the speaker)
| 1. | David Álvarez-Martínez
|
| Industrial Engineering, Universidad de Los Andes | |
| 2. | Francisco Parreño
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| Mathematics, Universidad de Castilla-La Mancha | |
| 3. | Germán Fernando Pantoja Beanvides
|
| Industrial Engineering, Universidad de los Andes |
Abstract
This study addresses the Container Loading Problem (CLP) by incorporating practical constraints such as valid box orientations, multi-drop loading, load-bearing, and vertical stability into a hybrid algorithm that combines the Greedy Randomized Adaptive Search Procedure (GRASP) with Beam Search. A key innovation of this approach is the use of Static-Mechanical-Equilibrium (SME) equations to model load-bearing and stability. Since SME equations can result in underdetermined systems, this study proposes a novel solution by introducing additional equations that distribute an item's weight based on the contact area of its supporting boxes. This methodology enables partial support and the placement of overhanging items, increasing packing flexibility. Furthermore, a merging-and-expanding procedure for maximal spaces enhances space utilization by reducing redundancy and expanding available packing areas throughout the process. Computational experiments demonstrate that the proposed method performs competitively with state-of-the-art approaches, achieving superior results in certain instances. These findings highlight the effectiveness of integrating SME-based stability modeling, partial support, and space optimization within a GRASP-Beam Search framework to address complex CLP scenarios.
Keywords
- Combinatorial Optimization
- Logistics
- Metaheuristics
Status: accepted
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