globalMOO is a software API designed to optimize multiple objectives using self-learning agents that can solve multi-outcome problems and optimize various models, including black box AI models.
Features
Multi-Outcome Optimization
Efficiently solves multiple objectives simultaneously using a multithreaded approach without human intervention.
API Integration
Easy integration with just five required endpoints for various programming languages, allowing quick implementation.
Model Agnostic
Can handle any predictive algorithm, including complex black box models, eliminating the need for simplification.
Real-Time Optimization
Provides real-time optimization through a unique reusable knowledge repository.
No Subjective Weight Assignments
Offers user-independent results by eliminating the dependency on subjective judgments during optimization.
Multi-Objective Optimization
Efficiently solves multiple objectives, even when they are in different units and scales, without user intervention.
Inverse Problem Solving
Specializes in calculating input variables that achieve specified output objectives.
Data-Efficient Algorithm
Requires fewer evaluations of models for quick and reliable outcomes, even with numerous objectives.
API and SDK
Offers seamless integration options including a Python SDK and web API for easy interaction with various systems.
Computational Scalability
Handles hundreds of input variables and objectives without extensive computing resources.