非同类机极小化最大完工时间的保密排序问题  

Privacy-preserving scheduling model for minimizingthe makespan on unrelated parallel machines

在线阅读下载全文

作  者:李好好 Li Haohao(School of Data Sciences,Zhejiang University of Finance and Economics,Hangzhou 310018,China)

机构地区:[1]浙江财经大学数据科学学院,浙江杭州310018

出  处:《纯粹数学与应用数学》2021年第2期243-252,共10页Pure and Applied Mathematics

基  金:国家自然科学基金(11701506);浙江省自然科学基金(LY21A010021).

摘  要:提出并研究了一类非同类机的极小化最大完工时间的保密排序问题Rm||Cmax.该问题的模型参数分为若干组,每个组都由一个不愿意共享或公开自己数据的单位所拥有.基于随机矩阵变换构造了一个不泄露私有数据且与原问题等价的安全规划模型,求解该安全模型可以获得问题的最优解,而且各单位的隐私数据仍然保持不被泄露.In this paper the scheduling problem Rm||Cmax is cast in a privacy-preserving framework.Consider the situation that the parameters in problem Rm||Cmax are partitioned into groups.Each group is owned by a distinct private entity that is unwilling to share or make public its own data.We construct a secure program based on the privately held data without revealing it by employing random matrix transformation.The secure program has the same optimal minimum value as the original mixed 0-1 linear program model of the problem Rm||Cmax,and the optimal solution to the secure program is publicly generated and is available to all entities.The 0-1 components in optimal solution to the secure program are coincident to those in optimal solution to the original solution.

关 键 词:排序 0-1规划 隐私保护 安全规划 

分 类 号:O157[理学—数学] O22[理学—基础数学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象