The invention discloses a
combinatorial optimization automatic modeling-oriented training data generation method and
system, and the method comprises the steps: receiving a
problem description text, extracting key information through semantic analysis and knowledge reasoning, and constructing a structured
optimization problem representation; reading the structured representation, extracting a target function component from the binary
label matrix, extracting a constraint function component from the
constraint relation adjacent matrix, extracting a variable definition component from the variable dependency matrix, and integrating the components to form a model component set; a value interval parameter is generated for the variable, a coefficient parameter is generated for the
constraint matrix, a weight parameter is generated for the target function, and a parameterized model instance is obtained; and applying corresponding templates to scene elements, variables and constraint descriptions to generate a
problem description text. Through the systematic
information extraction and parameter generation method, automatic generation of high-quality training data is realized, and the diversity and practicability of the data are improved.