Efficient, scalable, combinatorial optimization engine

РЎloud-based optimization engine designed to solve combinatorial problems e.g.: transportation optimization, scheduling, last-mile delivery, field service engineers

Quality
According to customers feedback the improvements are in the range from 5% to 30% even if you switch from another optimization engine

Performance
Solve large-scale transportation logistics problems within 10-20 minutes. if you need even better performance - adjust configuration

Scalability
Easily scale in both size of the problem and time to find a solution by adding more CPUs/Memory to the configuration

Business challenges

• Transportation optimization
• Automated decision making
• Risk assessment and mitigation
• Reduce cost and mileage
• Improve service quality
• Last mile delivery
• Dynamic Planning and Routing
• Field Service Engineers & Merchandisers Scheduling
• Fleet and drivers optimization
• Express delivery services\Postal service
• Long-haul\ Multimodal transportation
• Cashpoints cash management

Veeroute quickly finds optimal solutions, is exceptionally flexible and scalable, may be used for dynamic planning.

Problem-specific optimization engine

Our optimization engine enables you to define the problem in business terms using problem-specific API. Just describe how your transportation system works and it will find solution.

More detail. Better results.

Optimization service takes into consideration many details of how your transportation system works to be able to find solutions which satisfies all the requirements/restrictions you may have.

Flexible. By design.

From the very beginning optimization engine was designed in a way to easily extend the functionality. Thus the engine can be customized, adjusted for solving a particular problem with highest possible quality and performance while still considering problem-specific restrictions.

AI analyzes input data and requirements to find the most appropriate combination of algorithms and heuristics to solve a problem efficiently and effectively.

Optimization criteria

You may use more optimization objectives than just cost and revenue. You may also optimize mileage, service level, reliability, fleet size, drivers as well as combine those criteria. There is no quotation, cash is the king but to be competitive on the contemporary market you should also care about other charastics you customers are interested in.

Machine learning

Almost everything is в??smartв?? now or has some в??AIв?? inside. It is difficult to distinguish if there is real AI behind this or this is just for marketing purposes without a clear description of the technology. Veeroute uses gradient boosting machine learning technique to analyse input data and find the best set of algorithms to solve a problem.

Handling uncertainty and stochastic

The World is uncertain and stochastic by nature and this is great but it influences the planning significantly. Without considering uncertainty and stochastic you cannot do accurate planning. A random event may completely destroy a plan or even the whole system. Thus optimization engine should be able to take those characteristics into account to be able to provide results which are implementable in the real world.

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