A Block-Based Heuristic Algorithm for the Three-Dimensional Nuclear Waste Packing Problem

TL;DR

This work tackles the 3D nuclear waste packing problem in real plant settings by introducing a block-based heuristic (BSNA) that uses beam search to assemble waste into blocks and place them in the disposal pool. By organizing items into blocks, using an overlapping-space representation, and scoring placements with a dose-aware objective, the method improves space utilization while reducing cumulative dose exposure, as demonstrated on a 1600-instance synthetic benchmark drawn from real data and standard BPP datasets. The authors provide extensive experiments, revealing how a tunable parameter $\alpha$ balances volume efficiency and dose minimization, and show that longer search times can further enhance packing quality without increasing dose. Publicly available code and data support reproducibility and enable broader exploration of the approach in nuclear-waste management contexts.

Abstract

In this study, we present a block-based heuristic search algorithm to address the nuclear waste container packing problem in the context of real-world nuclear power plants. Additionally, we provide a dataset comprising 1600 problem instances for future researchers to use. Experimental results on this dataset demonstrate that the proposed algorithm effectively enhances the disposal pool's space utilization while minimizing the radiation dose within the pool. The code and data employed in this study are publicly available to facilitate reproducibility and further investigation.

Figures (7)

• Figure 1: partial space
• Figure 2: overlapping space.
• Figure 3: Block connection in three directions.
• Figure 4: Space update.
• Figure 5: Spatial utilization rate (%) under varying $\alpha$.