Proof of Concept — Universal Optimization Engine (QαT)
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Updated
Aug 3, 2026 - Python
Proof of Concept — Universal Optimization Engine (QαT)
A full-stack constraint optimization platform that automates complex, multidimensional scheduling. Powered by a custom C++ optimization engine and Google OR-Tools (CP-SAT), the system evaluates numerous hard and soft constraints simultaneously to generate conflict-free, highly optimized schedules in seconds.
AI-powered energy optimization platform with intelligent consumption analysis, adaptive learning, tariff prediction, and autonomous cost-saving recommendations.
A high-performance optimization engine designed to solve complex combinatorial problems. This solver implements custom selection, crossover, and mutation strategies to evolve optimal solutions for tasks like scheduling, resource allocation, and pathfinding.
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