Method and system for optimization and personalization of search results according to preferences and mandatory constraints

A system comprising:

• one or more memories having computer-readable instructions stored therein;
• and
• one or more processors configured to execute the computer-readable instructions to:
• collect input from at least one of software systems or one or more users, the input comprising one or more of unstructured input including at least one of natural language or voice, structured representations, input from third-party systems, or inputs from autonomous software agents;
• transform the input into one or more of mandatory constraints, soft constraints, or at least one preference, including at least one preference, on evaluation criteria for candidate solutions, wherein the evaluation criteria including the at least one preference are partially ordered and representable through a directed acyclic graph (DAG), wherein nodes of the DAG represent the preferences;
• determine weights for the evaluation criteria using a function and associate the weights with nodes of the DAG to determine a partial ordering of the weights consistent with a topological order of the DAG, wherein the weights are determined such that, for any node in the DAG, the weight of that node is separated from an aggregate of the weights of all nodes at lower levels in the topological order by a margin ensuring that preferential influence on an optimality score attributable to any single node is not matched or exceeded by any combination of preferential influences attributable to nodes at lower levels in the DAG;
• identify candidate solutions that satisfy any mandatory constraints on the evaluation criteria;
• determine and associate the optimality score with each candidate solution based on presence of preferential elements representable via the DAG in the candidate solutions, wherein the optimality score enables an ordering of the candidate solutions that ensures at least two properties are satisfied, the at least two properties including (i) the candidate solutions with a highest score are equally optimal, and (ii) the candidate solutions with a same score are equivalent;
• and
• order and return the candidate solutions.

One or more non-transitory computer-readable media comprising computer-readable instructions, which when executed by one or more processors, cause the one or more processors to:

• collect input from at least one of software systems or one or more users, the input comprising one or more of unstructured input including at least one of natural language or voice, structured representations, input from third-party systems, or inputs from autonomous software agents;
• transform the input into one or more of mandatory constraints, soft constraints, or at least one preference on evaluation criteria for candidate solutions, wherein the evaluation criteria including the at least one preference are partially ordered and representable through a directed acyclic graph (DAG), wherein nodes of the DAG represent the at least one preference;
• determine weights for the evaluation criteria using a function and associate the weights with nodes of the DAG to determine a partial ordering of the weights consistent with a topological order of the DAG, wherein the weights are determined such that, for any node in the DAG, the weight of that node is separated from an aggregate of the weights of all nodes at lower levels in the topological order by a margin ensuring that preferential influence on an optimality score attributable to any single node is not matched or exceeded by any combination of preferential influences attributable to nodes at lower levels in the DAG;
• identify candidate solutions that satisfy any mandatory constraints on the evaluation criteria;
• determine and associate the optimality score with each candidate solution based on presence of preferential elements representable via the DAG in the candidate solutions, wherein the optimality score enables an ordering of the candidate solutions that ensures at least two properties are satisfied, the at least two properties including (i) the candidate solutions with a highest score are equally optimal, and (ii) the candidate solutions with a same score are equivalent;
• and
• order and return the candidate solutions.