Scheduling with uncertain resources:

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Scheduling with uncertain resources Representatio
n and utility function
Ulas Bardak, Eugene Fink, and Jaime Carbonell
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Purpose

• Automation of office tasks, such as scheduling
  and resource allocation

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Challenges

• Intelligent performance ofoffice-management tasks

• Dealing with uncertaintyand unexpected situations

• Collaboration with users

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Conference planning

• Scheduling of talks at a conference,
• and related allocation of rooms and
• equipment, in a crisis situation.

DEMO

• Unexpected major change inspace availability
  for example,closing of a building

• Continuous stream of minor changesfor example,
  schedule changes and unforeseen equipment needs

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Architecture
Top-level control and learning
Processnew info
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Uncertainty
The system allows uncertainty in the
representation of all variables and functions in
optimization problems.

• Uncertain nominals

• Uncertain integers

• Uncertain utility

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Uncertain nominals
An uncertain nominal value is either a complete
unknown or a set of possible values and their
probabilities.
ExampleWe have ordered vegetarian meals, but
there is a chance that we will receive meals of a
wrong type.
Meal-type 0.90 chance vegetarian 0.05
chance regular 0.05 chance vegan
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Uncertain integers
An uncertain integer is either a complete unknown
or a probability-density function represented by
a set of uniform distributions.
ExampleAn auditorium has about 600 seats.
Room-size 0.2 chance 450..549 0.6 chance
550..650 0.2 chance 651..750
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Uncertain utilities
An uncertain utility function may be represented
in three ways.

• Complete unknown

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Optimization
The optimization algorithm is based on randomized
hill-climbing.

• Search for a schedule with the greatest expected
  quality

• At each step, reschedule one event

• Stop after finding a local maximumor reaching a
  time limit

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Experiments
without uncertainty
with uncertainty
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Conclusions
Results

• Optimization based on uncertainresources and
  constraints
• Collaboration with the user