The cross-organizational data has the typical characteristics of big data in collaborative optimization decision-making

such as distributedness

heterogeneity

and privacy etc. Secure multiparty computation(SMC) is a privacy-preserving algorithm

based on collaborative mechanisms or protocols. However

the methods typically used

such as monotone span program

cannot get rid of the computational complexity. It discussed two kinds of problems in collaborative optimization decision

and proposed secure multi-party computation protocols for the privacy-preserving of constraint parameters and decision variables. Then

it gave security proof. The results show that the SMC protocols can reduce the computational complexity of collaborative optimization decisions

and computation of some private information can be completed without transferred processing.