for Logistics & Shipping
Quantum-enhanced generative AI has the potential to transform optimization strategies for supply chain design, routing, scheduling, and disruption management. With increased efficiency, even a 5-10% overall reduction in supply chain costs would amount to $18 billion to $35 billion annually, according to McKinsey.
Delivery Routing and Scheduling
Routing and scheduling problems are widespread throughout the shipping and logistics industry. They ask: given a limited set of resources and time frame, what is the most efficient plan to execute the delivery of goods from their source to their destination? It may seem simple, but the problem quickly becomes impractical for classical computers to solve as the number of destinations increases. While the industry has developed heuristic algorithms that provide satisfactory solutions, there is still room for improvement. Doing so would save millions in fuel costs and people hours, increase revenue, and reduce harmful emissions.
Zapata’s Generator-Enhanced Optimization (GEO) technique has a demonstrated ability to provide an advantage for complex combinatorial optimization problems such as problems arising from routing and scheduling deliveries. Using quantum or quantum-inspired generative machine learning models, it learns from and improves upon the solutions generated by classical solvers. As quantum computers become more powerful, this technique will only become more effective in optimizing supply chains, inventory management, and shipping and delivery networks.Learn more about GEO
Applications for Logistics and Shipping
Supply Chain Design
Supply Chain Design
Supply Chain Optimization
Optimize the selection of suppliers, distributors, and vendors for product quality, costs, delivery times, and demand coverage using generator-enhanced optimization (GEO).
Facility Location Optimization
Optimize the location of facilities in the supply chain for capacitated and uncapacitated systems using quantum-enhanced prescriptive analytics.
Reverse Logistics Optimization
Optimize logistics networks for recycling, reuse, disposal, and product recalls using quantum or quantum-inspired machine learning techniques.
Optimize the design of warehouses as well as order-picking scheduling and routing to increase efficiency using generator-enhanced optimization (GEO).
Market Demand Forecasting
Model market demand for replenishment to reduce inventory stock-outs and support production scheduling using quantum-enhanced machine learning techniques.
Bullwhip Effect Mitigation
Predict spikes in demand that could trigger a bullwhip using quantum-enhanced predictive analytics.
Inventory Policy Optimization
Design inventory policies optimized for minimizing costs across multiple product families using GEO.
Workforce Scheduling Optimization
Optimize workforce scheduling to balance workloads for multi-commodity teams using quantum or quantum-inspired techniques.
Delivery Routing Optimization
Optimize vehicle routing for delivery operations to reduce costs and shorten delivery times using quantum-enhanced prescriptive analytics.
Predict and mitigate the effects of irregular operations (IROPs), such as extreme weather, using quantum-enhanced machine learning.
Fuel & Energy Optimization
Optimize vehicle control to minimize fuel consumption using generator-enhanced optimization (GEO).
Use Case Timeline (est.)
Top 5 Food & Beverage Company
An international beverage distributor routes drinks to over 700,000 vending machines in a territory worth $5.5B in revenue per year. Optimizing this distribution network would increase revenue, decrease fuel costs, and shrink the company’s carbon footprint.
Zapata used Orquestra® to upgrade the company’s classical delivery operations to support faster, more efficient daily routing computation. This enabled the company to begin operations ~45 minutes earlier each day, saving time and money in operations.
Orquestra® Benefits for Logistics and Shipping
Leverage the heterogenous compute resources best suited for your tasks, without getting locked into any one hardware platform. Deploy across hybrid backends at enterprise scale.
Data Management & Velocity
Store, retrieve, and analyze large datasets. Streamline data management from ingestion to export to accelerate data velocity.
Keep what works now. Integrate existing and future solutions with a framework optimized for extensibility, interoperability, and innovation.
Workflow Development and Deployment
One unified platform to go from research to development to deployment with extensible, scalable, modular workflows.
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