Chapter 3. Use Cases and Examples

3.1. Examples Overview

Planner has several examples. In this manual we explain mainly using the n queens example and cloud balancing example. So it's advisable to read at least those sections.
The source code of all these examples is available in the distribution zip under examples/sources and also in git under optaplanner/optaplanner-examples.

Table 3.1. Examples Overview

ExampleDomainSizeCompetition?Special features used
N queens
  • 1 entity class
  • 1 variable
  • Entity <= 256
  • Value <= 256
  • Search space <= 10^616
None
Cloud balancing
  • 1 entity class
  • 1 variable
  • Entity <= 2400
  • Value <= 800
  • Search space <= 10^6967
  • No
  • Defined by us
Traveling salesman
  • 1 entity class
  • 1 chained variable
  • Entity <= 980
  • Value <= 980
  • Search space <= 10^2927
Dinner party
  • 1 entity class
  • 1 variable
  • Entity <= 144
  • Value <= 72
  • Search space <= 10^310
  • Unrealistic
  • Decision Table spreadsheet (XLS) for score constraints
Tennis club scheduling
  • 1 entity class
  • 1 variable
  • Entity <= 72
  • Value <= 7
  • Search space <= 10^60
  • No
  • Defined by us
Course timetabling
  • 1 entity class
  • 2 variables
  • Entity <= 434
  • Value <= 25 and <= 20
  • Search space <= 10^1171
Machine reassignment
  • 1 entity class
  • 1 variable
  • Entity <= 50000
  • Value <= 5000
  • Search space <= 10^184948
Vehicle routing
  • 1 entity class
  • 1 chained variable
  • 1 shadow entity class
  • 1 automatic shadow variable
  • Entity <= 134
  • Value <= 141
  • Search space <= 10^285
Vehicle routing with time windows
Extra on Vehicle routing:
  • 1 shadow variable
  • Entity <= 1000
  • Value <= 1250
  • Search space <= 10^3000
Extra on Vehicle routing:
Project job scheduling
  • 1 entity class
  • 2 variables
  • 1 shadow variable
  • Entity <= 640
  • Value <= ? and <= ?
  • Search space <= ?
Hospital bed planning
  • 1 entity class
  • 1 nullable variable
  • Entity <= 2750
  • Value <= 471
  • Search space <= 10^6851
Exam timetabling
  • 2 entity classes (same hierarchy)
  • 2 variables
  • Entity <= 1096
  • Value <= 80 and <= 49
  • Search space <= 10^3374
Employee rostering
  • 1 entity class
  • 1 variable
  • Entity <= 752
  • Value <= 50
  • Search space <= 10^1277
Traveling tournament
  • 1 entity class
  • 1 variable
  • Entity <= 1560
  • Value <= 78
  • Search space <= 10^2951
  • Unrealistic
  • TTP
Cheap time scheduling
  • 1 entity class
  • 2 variables
  • Entity <= 500
  • Value <= 100 and <= 288
  • Search space <= 10^20078
  • Nearly realistic
  • ICON
Investment
  • 1 entity class
  • 1 variable
  • Entity <= 11
  • Value = 1000
  • Search space <= 10^4
  • No
  • Defined by us
A realistic competition is an official, independent competition:
  • that clearly defines a real-word use case
  • with real-world constraints
  • with multiple, real-world datasets
  • that expects reproducible results within a specific time limit on specific hardware
  • that has had serious participation from the academic and/or enterprise Operations Research community
These realistic competitions provide an objective comparison of Planner with competitive software and academic research.