. Implement a random starts local search algorithm for minimizing the AIC for the baseball salary regression problem. Model your algorithm after Example 3.3. a. Change the move strategy from steepest...

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Implement a random starts local search algorithm for minimizing the AIC for the baseball salary regression problem. Model your algorithm after Example 3.3.

a.
Change the move strategy from steepest descent to immediate adoption of the first randomly selected downhill neighbor.

b.
Change the algorithm to employ 2-neighborhoods, and compare the results with those of previous runs.

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Implement a tabu algorithm for minimizing the AIC for the baseball salary regression problem. Model your algorithm after Example 3.7.

a.
Compare the effect of using different tabu tenures.

b.
Monitor changes in AIC from one move to the next. Define a new attribute that signals when the AIC change exceeds some value. Allowthis attribute to be included on the tabu list, to promote search diversity.

c.
Implement aspiration by influence, overriding the tabu of reversing a low-influence move if a high-influence move is made prior to the reversal. Measure influence with changes in
R2.