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Research on online mixed palletizing strategy of robotic arms for multi-SKU scenarios
- 1 Yunnan University of Finance and Economics
- 2 Yunnan University of Finance and Economics
- 3 University of Science and Technology Beijing
* Author to whom correspondence should be addressed.
Abstract
In intelligent warehousing and transportation processes, the centralization of material units significantly enhances storage and handling efficiency. Among these, the centralized unitization of material pallets is in high demand and widely applied in practical operations. In multi-SKU scenarios, achieving efficient palletizing—particularly online mixed palletizing—poses a major challenge in logistics operations. This process aims to save manpower while ensuring operational efficiency. To address this issue, this paper presents a combined heuristic algorithm that integrates an anthropomorphic heuristic algorithm with a greedy algorithm incorporating local perturbations. The proposed approach accounts for constraints such as mass, volume, center of gravity, non-overlapping placement, and stability. Experimental results demonstrate that this algorithm effectively resolves the palletizing challenges for multi-SKU goods, significantly reducing space waste.
Keywords
online palletizing, multi-SKU, anthropomorphic heuristic algorithm, greedy algorithm
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Cite this article
Jin,G.;Ding,X.;Jin,D. (2025). Research on online mixed palletizing strategy of robotic arms for multi-SKU scenarios. Advances in Engineering Innovation,15,26-34.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Journal：Advances in Engineering Innovation
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