anchor.diff:  == 6. Be fair (load balancing)
   
   When distributing work across humans (or machines), don't use averages.
  -Instead, the worst off human (or machine) counts the most.
  +Instead, *the worst off human (or machine) counts the most.*
   
   For example in employee rostering we want to distribute the shifts evenly,
   but we can't make it perfectly fair due to skill and other hard constraints.
  
positive.code: == 5. Account for overconstrained planning
  
  It can happen that there aren't enough resources to solve a planning problem without breaking a hard constraint.
  In that case, it's often better to leave some entities unassigned (as little as possible of course).
  
  For example in employee rostering, when we need to assign 4 late shifts on the same day and we only have 3 employees,
  it's better to leave 1 shift unassigned than to assign an employee to 2 shifts at the same time.
  
negative.code: 
  There are 7 common ways to fail your optimization project:
  
  . Ignore the user's plan
  
  . Neglect a hard constraint
  
  . Decide all score weights up front
  
  . Change tentative plans drastically
  
  . Presume there is always a feasible plan
  
  . Average out fairness or load balancing
  
  . Focus on only 1 stakeholder
  
  Let's take a look at each one in detail and *the 7 ways to make your project a success*:
  
  
  == 1. Keep the user in control
  