Introduction
The Pick-up and Delivery Routing model is one of Timefold’s planning AI models and is available on the Timefold Platform.
The Pick-up and Delivery Routing model assigns pick-ups and deliveries to drivers so that multiple pick-ups and deliveries can be made at the same time. The model balances the driver’s vehicle capacity, current load, and demand while minimizing driving time and customer wait times.
The model runs on the Timefold Platform and the application includes Timefold Enterprise Solver, a scalable optimization engine that can solve complex constraint satisfaction problems.
The Pick-up and Delivery Routing model includes constraints for:
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Scheduling customer pick-ups and deliveries when customers have agreed to be available.
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Assigning drivers with the right skills for the jobs.
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Prioritizing jobs and meeting job requirements.
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Fairly assigning work to drivers and respecting their work hours.
To learn more about individual constraints, see the Driver resource constraints and Job requirements and tags guides.
Constraints have configurable weights, making them adjustable to meet different business goals and priorities.
The integrated maps service provides real-world routing and optimizing for the shortest travel time or travel distance.
The real time planning API makes plans adaptable when unforeseen events inevitably occur, and the recommendations API can help you figure out which drivers to assign to which jobs.
The REST API layer is defined on top of the model and serves as a communication point with the engine to provide a stable interface that allows you to manage the lifecycle of the optimization problem, from submitting the initial dataset to retrieving the final solution.
Introduction for integration & application developers
Backend developers, integration engineers, full-stack developers, and technical consultants implement the model in an application or workflow.
| Concern | Documentation |
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How to get a first working solution quickly |
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Correct API usage |
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Understanding available constraints and features |
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Debugging invalid inputs or unexpected results |
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How the model supports reacting to unexpected events and replanning with the least amount of disruption |
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Performance tuning |
Introduction for platform & enterprise architects
Enterprise architects, solution architects, security architects, IT governance leads, and platform owners are responsible for system integration, compliance, and long-term maintainability.
| Concern | Documentation |
|---|---|
How the model integrates into existing enterprise systems |
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API contracts, and long-term stability |
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Authentication, authorization, and request integrity |
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Auditability of configuration changes |
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Risk profile, product security, data security and general trust |
Introduction for product, business & decision makers
Product managers, project managers, business analysts, operations managers, and executives evaluate value, scope, and speed of delivery.
| Concern | Documentation |
|---|---|
What business problems the model solves |
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How results can be evaluated and explained to stakeholders |
Interpreting dataset results, Validating an optimized plan with Explainable AI |
How the model can support strategic decision making |
Uncovering inefficiencies in operational planning, Balancing different optimization goals |
Following up on new features |
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Whether the model can evolve with changing business needs |
Next
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See the full API spec or try the online API.
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Follow the Getting started guide.