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一种用于解决NP完全问题的特殊机器。

A special machine for solving NP-complete problems.

作者信息

Xu Jin, Yu Le, Yang Huihui, Ji Siyuan, Wu Pu, Zhang Yu, Yang Anqi, Li Quanyou, Li Haisheng, Zhu Enqiang, Shi Xiaolong, Shao Zehui, Leng Huang, Liu Xiaoqing

机构信息

School of Computer Science, Peking University, Beijing 100871, China.

School of Computer and Artificial Intelligence, Beijing technology and Business University, Beijing 100048, China.

出版信息

Fundam Res. 2025 Jun 6;5(4):1743-1749. doi: 10.1016/j.fmre.2025.05.010. eCollection 2025 Jul.

Abstract

A specialized computer named as the Electronic Probe Computer (EPC) has been developed to address large-scale NP-complete problems. The EPC employs a hybrid serial/parallel computational model, structured around four main subsystems: a converting system, an input/output system, and an operating system. The converting system is a software component that transforms the target problem into the graph coloring problem, while the operating system is designed to solve these graph coloring challenges. Comprised of 60 probe computing cards, this system is referred to as EPC60. In tackling large-scale graph coloring problems with EPC60, 100 3-colorable graphs were randomly selected, each consisting of 2,000 vertices. The state-of-the-art mathematical optimization solver achieved a success rate of only 6%, while EPC60 excelled with a remarkable 100% success rate. Additionally, EPC60 successfully solved two 3-colorable graphs with 1,500 and 2,000 vertices, which had eluded Gurobi's attempts for 15 days on a standard workstation. Given the mutual reducibility of NP-complete problems in polynomial time theoretically, the EPC stands out as a universal solver for NP-complete problem. The EPC can be applied to various problems that can be abstracted as combinatorial optimization issues, making it relevant across multiple domains, including supply chain management, financial services, telecommunications, energy systems, manufacturing, and beyond.

摘要

一种名为电子探针计算机(EPC)的专用计算机已被开发出来,用于解决大规模的NP完全问题。EPC采用混合串行/并行计算模型,围绕四个主要子系统构建:一个转换系统、一个输入/输出系统和一个操作系统。转换系统是一个软件组件,它将目标问题转换为图着色问题,而操作系统旨在解决这些图着色挑战。该系统由60个探针计算卡组成,被称为EPC60。在用EPC60解决大规模图着色问题时,随机选择了100个可三色着色的图,每个图由2000个顶点组成。最先进的数学优化求解器的成功率仅为6%,而EPC60则以100%的显著成功率脱颖而出。此外,EPC60成功解决了两个分别有1500个和2000个顶点的可三色着色图,这两个图在标准工作站上让Gurobi尝试了15天都未能解决。鉴于理论上NP完全问题在多项式时间内相互可归约,EPC作为NP完全问题的通用求解器脱颖而出。EPC可应用于各种可抽象为组合优化问题的问题,使其在多个领域都具有相关性,包括供应链管理、金融服务、电信、能源系统、制造业等等。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c84/12327857/c4680de23908/ga1.jpg

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