anchor.diff:  
   This solver configuration consists of three parts:
   
  -. **Domain model configuration**
  -
  -*What can Planner change?*
  +. *Domain model configuration*: _What can Planner change?_
   +
   We need to make Planner aware of our domain classes. In this configuration, it will automatically scan all classes in your classpath (for a `@PlanningEntity` or `@PlanningSolution` annotation):
   +
  -
   [source,xml,options="nowrap"]
   ----
     <scanAnnotatedClasses/>
   ----
  -. **Score configuration** 
   
  -*How should Planner optimize the planning variables? What is our goal?*
  +. *Score configuration*: _How should Planner optimize the planning variables? What is our goal?_
   +
   Since we have hard and soft constraints, we use a ``HardSoftScore``. But we need to tell Planner how to calculate the score, depending on our business requirements. Further down, we will look into two alternatives to calculate the score: using an easy Java implementation, or using Drools DRL.
   +
  
positive.code: + 
  The default algorithms will already easily surpass human planners and most in-house implementations.
  Use the <<benchmarker,Benchmarker>> to <<powerTweaking,power tweak>> to get even better results.
  
  
negative.code:     <!--<scoreDrl>org/optaplanner/examples/cloudbalancing/solver/cloudBalancingScoreRules.drl</scoreDrl>-->
    </scoreDirectorFactory>
  ----
  
  . *Optimization algorithms configuration*: _How should Planner optimize it?_
  +
  In this case, we use the default <<optimizationAlgorithms,optimization algorithms>> (because no explicit optimization algorithms are configured) for 30 seconds:
  +
  [source,xml,options="nowrap"]
  ----
    <termination>
  