Facility site selection method and system based on encrypted position data

Abstract

The invention provides a facility site selection method and system based on encrypted position data, a clustering calculation party, an auxiliary calculation party and a plurality of position providers. The clustering calculation party and the auxiliary calculation party cannot collude, and an enterprise can obtain an equipment site selection result but cannot obtain position information of any client; the auxiliary computing party only provides an auxiliary computing service and cannot obtain an equipment site selection result, the position of a client, other intermediate results and relatedinformation; according to the method, the client encrypts the position data before sharing the position data, so that privacy is protected, an enterprise can perform clustering calculation by utilizing the encrypted position data, the construction position of the facility is obtained, and the accuracy of facility site selection is greatly improved.

Description

technical field [0001] The present disclosure relates to the technical field of facility location selection, in particular to a method and system for facility location selection based on encrypted location data. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] Facility location selection is an important issue that enterprises often need to face in decision-making. The location selection of facilities such as gas stations, cash machines, logistics centers, service outlets, and communication base stations is often related to the commercial interests of enterprises. One of the basic principles of facility siting is to allow a limited number of facilities to cover as wide a customer base as possible while minimizing the sum of the distances between all customers and their nearest facilities. [0004] The inventors of the present disclosure f...

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Problems solved by technology

[0004] The inventors of the present disclosure found that k-means clustering calculation based on the customer's location is a typical method to solve the above problems, but the customer's location data involves the customer's privacy, and the enterprise often has no right to obtain it, so the final location selection plan is often can not meet the requirements

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