Computing system for generating and optimizing schema-conformant object models

A computer-implemented method, comprising:

• obtaining input data from a plurality of data sources, the input data comprising multi-format data representations encoded in a structured, semi-structured, or unstructured format;
• processing the input data using machine-executed parsing logic to derive a structured rule set defining spatial relationships and constraint conditions;
• generating, based on the structured rule set, one or more schema-conformant object representations comprising parametric assemblies of spatial components;
• in response to receiving a configuration payload comprising user selections or preference parameters,
• translating the user selections or preference parameters into constraint objects,
• combining the constraint objects with rule-based conditions derived from the input data to generate combined constraint conditions, and
• applying the combined constraint conditions to the one or more schema-conformant object representations using machine-executed constraint resolution logic;
• generating candidate object models by iteratively modifying the one or more schema-conformant object representations under the structured rule set, the iteratively modifying comprising at least one of repositioning a spatial component, adjusting a dimensional parameter, or reconfiguring an adjacency relationship;
• computing performance values for the candidate object models using machine-executed evaluation logic that applies quantitative analysis of spatial efficiency and constraint compliance;
• and
• selecting an optimized object model from the candidate object models based on computed performance values.

A non-transitory computer readable storage medium storing instructions that, when executed by at least one processor of a computing system, causes the computing system to:

• obtain input data from a plurality of data sources, the input data comprising multi-format data representations encoded in a structured, semi-structured, or unstructured format;
• process the input data using machine-executed parsing logic to derive a structured rule set defining spatial relationships and constraint conditions;
• generate, based on the structured rule set, one or more schema-conformant object representations comprising parametric assemblies of spatial components;
• in response to receiving a configuration payload comprising user selections or preference parameters,
• translate the user selections or preference parameters into constraint objects,
• combine the constraint objects with rule-based conditions derived from the input data to generate combined constraint conditions, and
• apply the combined constraint conditions to the one or more schema-conformant object representations using machine-executed constraint resolution logic;
• generate candidate object models by iteratively modifying the one or more schema-conformant object representations under the structured rule set, the iteratively modifying comprising at least one of repositioning a spatial component, adjusting a dimensional parameter, or reconfiguring an adjacency relationship;
• compute performance values for the candidate object models using machine-executed evaluation logic that applies quantitative analysis of spatial efficiency and constraint compliance;
• and
• select an optimized object model from the candidate object models based on computed performance values.