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GENERATING A MIXED INTEGER LINEAR PROGRAMMING MATRIX FROM AN ANNOTATED ENTITY-RELATIONSHIP DATA MODEL AND A SYMBOLIC MATRIX
GENERATING A MIXED INTEGER LINEAR PROGRAMMING MATRIX FROM AN ANNOTATED ENTITY-RELATIONSHIP DATA MODEL AND A SYMBOLIC MATRIX
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机译：从带注释的实体关系数据模型和符号矩阵生成混合整数线性规划矩阵
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摘要
Programmatically generating a mixed integer linear programming (“MIP”) matrix, which can then be solved to provide an optimization, based on an annotated entity/relationship data model and a symbolic matrix. The annotated data model identifies one or more outputs of the optimization. The symbolic matrix provides one or more constraints that provide requirements under which the optimization is solved. Outputs of the optimization are represented as variables, inputs of the optimization are represented as constants, and primary keys from the data model are represented as indexes. The constraints are expressed using the variables, constants, and indexes. A MIP matrix is generated from the symbolic matrix, and is then solved by a MIP solver. The output of the MIP solver is used to update a corresponding data structure of the data model.
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