### Solving the Examination problem part 2: score function

This is the second part in a blog series about drools-solver and the Examination problem. If you haven’t done so, read Solving the Examination problem: Domain diagram first.

Each possible solution has a score. Before we try to find the best solution, we need a way to calculate the score of a solution. And that’s where the drools rule engine comes into play.

So the current working solution is asserted into the working memory (based on it’s getFacts() method) and a number of score rules are fired upon it. Generally, each (hard or soft) constraint translates into a single score rule.

For example, this is the score rule to penalize all exams for which the period duration doesn’t suffice.

// More time required during a period than available in that period.rule "periodDurationTooShort"    when        // Any exam who's duration is longer that it's period duration ...        $exam : Exam(eval(topicDuration > periodDuration)); then // ... is penalized hard. insertLogical(new IntConstraintOccurrence("periodDurationTooShort", ConstraintType.NEGATIVE_HARD,$exam.getTopicStudentSize(),                $exam));end Of course, some rules are more complicated, like the score rule to penalize all conflicting exams in a row: // Two exams in a row which share studentsrule "twoExamsInARow" when // When 2 in row exams are penalized, ...$institutionalWeighting : InstitutionalWeighting(twoInARowPenality != 0);        // ..., any 2 exams that share students ...        $topicConflict : TopicConflict($leftTopic : leftTopic, $rightTopic : rightTopic); // ... of which the periods ...$leftExam : Exam(topic == $leftTopic,$leftPeriod : period);        $rightExam : Exam(topic ==$rightTopic, $rightPeriod : period); // ... occur on the same day ... eval($leftPeriod.getDayIndex() == $rightPeriod.getDayIndex()); // ... and are successive, ... eval(Math.abs($leftPeriod.getPeriodIndex() - $rightPeriod.getPeriodIndex()) == 1); then // ..., are penalized softly. insertLogical(new IntConstraintOccurrence("twoExamsInARow", ConstraintType.NEGATIVE_SOFT,$topicConflict.getStudentSize() * $institutionalWeighting.getTwoInARowPenality(),$leftExam, \$rightExam));end

Using the drools rule engine to calculate the score has a bunch of advantages:

• The constraint score rules are easier to implement, once you get the hang of the DRL pattern syntax.
• The implementations of the constraints are isolated from each other.
So adding extra constraints is easy and scalable.
• If the working solution changes into an adjacent solution (for example due to a solver move), drools does forward-chaining. This means you get delta based score calculation without any effort. That’s a huge performance boost without breaking a sweat.

Now that we know how to calculate the score of solution, we can recognize a good solution. In a next blog we ‘ll take a look at finding the best solution we can find out of 10^5761 possible solutions.