TitanQ Use Cases
InfinityQ’s technology is ready to transform multiple industries.
Energy Grid Optimization
Problem:
Maximize green score while minimizing cost to source power from various power providers.
Inputs:
Power provider matrix, and interaction matrix between the providers.
Formulation possibilities:
Constrained power maximization problem.
Solution:
Real time grid optimization capabilities for grid rebalancing.
Minimize Total Cost
Maximise Total Green Score
Subject to Max/Min power from each plant
Supply Chain Optimization
Problem:
Build a robust supply chain that can meet customer deadlines to avoid costly penalties while withstanding potential shocks and minimizing costs.
Inputs:
Supplier Lead Times, Part delivery date, potential schedule disruptions.
Formulation possibilities:
Smart supply chain scheduling, with additional slack between steps and multi-supplier awareness.
Solution:
-Initial planning of robust schedule
-Method to replan given supply chain shock
Port Optimization
Problem:
Automated ports require advanced dynamic optimization capabilities to reroute cranes & containers effectively.
Inputs:
Crane & container availability for ships, demand expectations for ship arrivals.
Formulation possibilities:
On site/cloud planning of production capabilities using mixed-integer optimization platform.
Solution:
Real-time FPGA/GPU system capable for dynamic crane & container loading planning.
Portfolio Optimization
Problem:
Produce maximum returns for a given associated risk value.
Inputs:
Asset expected returns and correlation data between assets.
Formulation possibilities:
Markowitz model-based risk minimization + maximum weight independent set.
Solution:
Direct asset allocation with efficient frontier generation of model.
Middle Mile Delivery
Problem:
Middle Mile Delivery. Set of trucks need to be routed between delivery hubs maximizing total profits while respecting constraints.
Inputs:
Connection graph and conflicts graph. Which routes may be taken, which can’t be taken together.
Formulation possibilities:
Set Cover with Weighted Vertices
Maximum Weight independent Set.
Solution:
Ising Model solver with ability to solve graphs with >10000 vertices.
