Solving planning problems with drools-solver

Abstract

Drools-solver combines a search algorithm with the power of the drools rule engine to solve planning problems, such

Employee shift rostering
Freight routing
Supply sorting
Lesson scheduling
Exam scheduling
The traveling salesmen problem
The traveling tournament problem

Drools-solver supports several search algorithms, such as simple local search, tabu search and simulated annealing. You can easily switch the search algorithm, by simply changing the configuration. There's even a benchmark utility which allows you to play out the different search algorithms against each other on your planning problem.

Drools-solver uses the drools rule engine to calculate the score, based on score rules. This allows you to easily add hard and soft constraints in your score function, simply by adding a score rule.

In this session, Geoffrey, main developer of drools-solver and member of the drools team, will first demonstrate some of the complex examples and then take you through the source code for solving an n queens puzzle with drools-solver.

Speaker

Geoffrey De Smet