Consider a maximization problem that is being solved by Simulated Annealing. Let the objective function value of the current state, s, be 1000. Let this state have 5 successors/neighbors: s1(950), s2(975), s3(1000), s4(1000), and s5(1050). The numbers in parentheses represent the corresponding objective function values. The current temperature is 100. The probability that the next state is: 1. s1 = [Select] 2. s2 = [Select] 3. s3 [Select] = 4. s4= [Select] [Select] 5. s5 0.778 0.121 0.156 0.2 0.606

Operations Research : Applications and Algorithms
4th Edition
ISBN:9780534380588
Author:Wayne L. Winston
Publisher:Wayne L. Winston
Chapter13: Decision Making Under Uncertainty
Section: Chapter Questions
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Consider a maximization problem that is being solved by Simulated Annealing. Let
the objective function value of the current state, s, be 1000. Let this state have 5
successors/neighbors: s1(950), s2(975), s3(1000), s4(1000), and s5(1050). The
numbers in parentheses represent the corresponding objective function values.
The current temperature is 100. The probability that the next state is:
1. s1 = [Select]
2. s2 = [Select]
3. s3 [Select]
=
4. s4= [Select]
[Select]
5. s5
0.778
0.121
0.156
0.2
0.606
Transcribed Image Text:Consider a maximization problem that is being solved by Simulated Annealing. Let the objective function value of the current state, s, be 1000. Let this state have 5 successors/neighbors: s1(950), s2(975), s3(1000), s4(1000), and s5(1050). The numbers in parentheses represent the corresponding objective function values. The current temperature is 100. The probability that the next state is: 1. s1 = [Select] 2. s2 = [Select] 3. s3 [Select] = 4. s4= [Select] [Select] 5. s5 0.778 0.121 0.156 0.2 0.606
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