Introduction

The Task Scheduling model is one of the Scheduling APIs available on the Timefold Platform.

The Task Scheduling model currently has Preview maturity. At this stage, backward-incompatible changes can still be introduced. For more information, see Model maturity and versioning.

Task Scheduling model assigns jobs to machines and employees with the goal of increasing the number of jobs that can be completed and minimizing the makespan.

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 Task Scheduling model includes constraints for:

  1. Minimize makespan.

  2. Assign jobs to the correct machines and employees.

  3. Manage job dependencies.

  4. Minimize the number of unassigned jobs.

  5. Manage job priorities.

For details about these and other constraints, see the Job service constraints and Machine and employee resource constraints guides.

Task Scheduling production schedule

Constraints have configurable weights, making them adjustable to meet different business goals and priorities.

The Real-time planning API makes plans adaptable when unforeseen events inevitably occur.

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.

1. Introduction for integration and application developers

Backend developers, integration engineers, full-stack developers, and technical consultants implement the model in an application or workflow.

Concern Documentation

How to get a first working solution quickly

Getting started: Hello world

Correct API usage

Using the API, Integration, Dataset lifecycle

Understanding available constraints and features

Job service constraints and Machine and employee resource constraints

How the model supports reacting to unexpected events and replanning

Real-time planning

Performance tuning

Configuration parameters and profiles

2. Introduction for platform and 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

Integration

API contracts, and long-term stability

Model maturity and versioning

Authentication, authorization, and request integrity

API keys, Member management and roles, Secrets management

Auditability of configuration changes

Reviewing the audit log

Risk profile, product security, data security and general trust

Trust

3. Introduction for product, business, and 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

Metrics and optimization goals

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

Changelog and Upgrading to the latest versions

Whether the model can evolve with changing business needs

Feature requests

Next