paper-with-me

홈 › Papers

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

2025-03-09 · Yajie Wen, Defu Zhang

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.

📄 PDF Abstract BibTeX arXiv:2503.08705

Code (0)

등록된 구현이 없습니다.

Tasks

Heuristic Search

Similar Papers 제목 키워드 기반

Gnowee: A Hybrid Metaheuristic Optimization Algorithm for Constrained, Black Box, Combinatorial Mixed-Integer Design

2018-04-15 · James Bevins, Rachel Slaybaugh

This paper introduces Gnowee, a modular, Python-based, open-source hybrid metaheuristic optimization algorithm (Available from https://github.com/SlaybaughLab/Gnowee). Gnowee is designed for rapid convergence to nearly g…

Metaheuristic Optimization

A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms

2010-12-02 · Zhouchen Lin, Siming Wei

Recent years have witnessed the popularity of using rank minimization as a regularizer for various signal processing and machine learning problems. As rank minimization problems are often converted to nuclear norm minimi…

Matrix Completion

Necessary and Sufficient Null Space Condition for Nuclear Norm Minimization in Low-Rank Matrix Recovery

2018-02-14 · Jirong Yi, Weiyu Xu

Low-rank matrix recovery has found many applications in science and engineering such as machine learning, signal processing, collaborative filtering, system identification, and Euclidean embedding. But the low-rank matri…

Collaborative Filtering

Truncated nuclear norm regularization for low-rank tensor completion

2019-01-07 · Shengke Xue, Wenyuan Qiu, Fan Liu, Xinyu Jin

Recently, low-rank tensor completion has become increasingly attractive in recovering incomplete visual data. Considering a color image or video as a three-dimensional (3D) tensor, existing studies have put forward sever…

Approximate Matrix Multiplication with Application to Linear Embeddings

2014-03-30 · Anastasios Kyrillidis, Michail Vlachos, Anastasios Zouzias

In this paper, we study the problem of approximately computing the product of two real matrices. In particular, we analyze a dimensionality-reduction-based approximation algorithm due to Sarlos [1], introducing the notio…

Dimensionality Reduction