Method and system for automated process optimization using a multi-agent artificial intelligence (ai) based optimization framework

A system for automated process optimization, comprising:

• a processor;
• a memory storing instructions that, when executed by the processor, cause the system to implement:
• a multi-agent artificial intelligence (AI) based optimization framework comprising:
• a plurality of AI agents, wherein each AI agent of the plurality of AI agents is configured to perform specific optimization-related operations, the plurality of AI agents comprising:
• a domain identifier and prompt generation agent configured to interface with a large language model (LLM) to analyze input process documentation and identify one or more optimization domains with corresponding optimization rationales;
• a formulator agent configured to generate one or more optimization problem specifications comprising sets, parameters, decision variables, objective functions, and constraints based on the identified optimization domains;
• a programmer agent configured to translate the optimization problem specifications into executable optimization code;
• an evaluator agent configured to validate optimization solutions and implement constraint adjustments;
• a supervisor agent operatively coupled to the plurality of AI agents, wherein the supervisor agent is configured to:
• receive the input process documentation via an interface;
• orchestrate sequential interactions between the plurality of AI agents to generate and validate the optimization solutions;
• verify intermediate outputs at each processing stage;
• and
• output the validated optimization solutions via the interface.