Welcome to JobShopLib's documentation!

Version: 1.0.0-alpha.2

JobShopLib is a Python package for creating, solving, and visualizing Job Shop Scheduling Problems (JSSP).

It follows a modular design, allowing users to easily extend the library with new solvers, dispatching rules, visualization functions, etc.

See this Google Colab notebook for a quick start guide!

Contents

• Install
  • Development
• Examples
  • Getting Started to Job Shop Lib
  • How Solutions are Represented
  • Solving the Problem
  • Dispatching Rules
    • Example Instance
    • Solving a Benchmark Instance
  • Disjunctive Graph representation
  • Load Benchmark Instances
  • Gannt Chart Creation: How to Save GIFs and Videos
  • The Agent-Task Graph representation
  • Feature Observers
  • RL Graph Environment: Learning from one instance
  • RL Graph Environment: Learning from many instances
  • Comparing Performance: Dispatcher Method vs. Observer Method for Unscheduled Operations
    • Setup
    • Method 1: Using dispatcher.unscheduled_operations()
    • Method 2: Using UnscheduledOperationsObserver
    • Results Analysis
    • Conclusion
• API
  • job_shop_lib
    • Operation
    • JobShopInstance
    • ScheduledOperation
    • Schedule
    • BaseSolver
    • job_shop_lib.benchmarking
    • job_shop_lib.constraint_programming
    • job_shop_lib.dispatching
    • job_shop_lib.exceptions
    • job_shop_lib.generation
    • job_shop_lib.graphs
    • job_shop_lib.reinforcement_learning
    • job_shop_lib.visualization

Indices and tables

• Index

• Module Index

• Search Page