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PLANNING UNDER UNCERTAINTY REGRET THEORY by Ahmed Aseeri * MINIMAX REGRET ANALYSIS It s a feeling measurable . MINIMAX REGRET ANALYSIS If chosen decision ... – PowerPoint PPT presentation

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1
PLANNING UNDER UNCERTAINTY
REGRET THEORY
 by   Ahmed Aseeri December 8, 2013
2
MINIMAX REGRET ANALYSIS
  • Its a feeling
  • measurable .

3
MINIMAX REGRET ANALYSIS
  • If chosen decision is the best ? Zero regret
  • Nothing is better than the best ? No negetive
    Regret

4
MINIMAX REGRET ANALYSIS
Motivating Example
  • Traditional way Maximize Averageselect A
  • Optimistic decision maker MaxiMax select C
  • Pessimistic decision maker MaxiMmin select
    D

5
MINIMAX REGRET ANALYSIS
Motivating Example
  • Calculate regret
  • find maximum regret
  • A regret 8 _at_ low market
  • C regret 9 _at_ low market
  • D regret 10 _at_ high market
  • B regret 7 _at_ medium market
  • MINIMAX ? B
  • In general, gives conservative decision
  • but not pessimistic.

6
MINIMAX REGRET ANALYSIS
Two-Stage Stochastic Programming Using Regret
Theory
7
MINIMAX REGRET ANALYSIS
Two-Stage Stochastic Programming Using Regret
Theory
where
subject to
,
subject to
,
8
MINIMAX REGRET ANALYSIS
Two-Stage Stochastic Programming Using Regret
Theory
9
MINIMAX REGRET ANALYSIS
Two-Stage Stochastic Programming Using Regret
Theory
where
subject to
,
subject to
,
10
MINIMAX REGRET ANALYSIS
Two-Stage Stochastic Programming Using Regret
Theory
11
MINIMAX REGRET ANALYSIS
Limitations on Regret Theory
  • It is not necessary that equal differences in
    profit would always correspond to equal amounts
    of regret

1000 - 1050 50 100 - 150 50
s1 s2 s3 Max. Regret
A 100 0 5 100
B 99 95 40 99
C 0 100 200 200
D 150 85 0 150
  • A small advantage in one scenario may lead to
    the loss of larger advantages in other scenarios.
  • May select different preferences if one of the
    alternatives was excluded or a new alternative
    is added.

12
CONCLUSION
Suggested improvements to minimax-regret
criterion
  • Minimizing the average regret instead of
    minimizing the maximum.

Upper Regret
52.5
97
150
117.5
s1 s2 s3 Max. Regret
A 100 0 5 100
B 99 95 40 99
C 0 100 200 200
D 150 85 0 150
Avrg. Regret
35
78
100
78.3
  • Minimizing the upper regret average instead of
    the maximum only.
  • Measure relative regret instead of absolute
    regret

13
END
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