The Schedule Crasher Exercise

The Schedule Crasher Exercise

  • This game helps you to understand some common concepts in project scheduling. The problem here is to "crash the schedule," that is, to complete it in less time than originally planned.
  • We have a project with 7 activities. Some activities must be completed before other activities can start:

What Makes This Interesting?

  • You can crash a schedule by adding people to help on the different project activities. There are two problems with this:
    • Each additional person speeds up completion of an activity but perhaps with less effect. This is called "decreasing returns to scale." In general, you are better to add additional people to different activities.
    • You can add people to an activity and shorten its duration but it doesn't speed up the project as a whole. That is because you sped up a "slack" activity: no other activity is waiting for it to complete. You are better to speed up "critical" activities: ones that prevent the project from completing early.

What's The Goal?

  • Your goal is to crash the schedule to 20 days:
    • ScheduleCrasherGoal

How Can You Do That?

  • Add people to activities (but not too many):
    • ScheduleCrasher33Days

Are You Ready to Play?

  • (Game appears on the next slide)

What To Avoid?

  • Don't add people to a 'slack' activity:
    • ScheduleCrasherActivity 4

Where to Focus?

  • Add people to 'critical' activities only. They are shown in red:
    • ScheduleCrasherActivity3

Can You Do Better Than This?

  • It took 20 people to crash the schedule. Is there a better solution?
    • ScheduleCrasherTargetAchieved

Follow the Guides

  • Reset personnel to zero and play again, but, this time, follow the guides:
    • ScheduleCrasherReset

The Guides Can Help

  • Using the Guides led us to a good solution quickly:
    • ScheduleCrasherGuidedSolution

What is the Trick?

  • The "Try Me!" guides were constructed using a technique called "marginal analysis." This is a common optimisation technique known by many names:
    • Incremental analysis
    • Greedy algorithm
    • Steepest descent
    • "Most bang for the buck"
  • This is just one of many techniques you will learn in the study of optimisation. It is not guaranteed to find the optimal solution but it is often easy to construct.

Learn More

  • We hope you enjoyed this module and would like to learn more about applications of probability and optimisation.
  • Please visit our website at SUTD Engineering Systems and Design