solu8 - This le contains the exercises hints and solutions...

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This fle contains the exercises, hints, and solutions For Chapter 8 oF the book ”Introduction to the Design and Analysis oF Algorithms,” 2nd edition, by A. Levitin. The problems that might be challenging For at least some students are marked by ± ; those that might be difficult For a majority oF students are marked by ² . Exercises 8.1 1. a. What does dynamic programming have in common with divide-and- conquer? b. What is a principal di±erence between the two techniques? 2. a. Compute C (6 , 3) by applying the dynamic programming algorithm. b. Is it also possible to compute C ( n,k ) by flling the algorithm’s dy- namic programming table column by column rather than row by row? 3. Prove the Following assertion made in the text while investigating the time efficiency oF the dynamic programming algorithm For computing C ( ) : ( k 1) k 2 + k ( n k ) Θ( nk ) . 4. a. What is the space efficiency oF Binomial, the dynamic programming algorithm For computing C ( ) ? b. Explain how the space efficiency oF this algorithm can be improved. (Try to make as much oF an improvement as you can.) 5. a. ²ind the order oF growth oF the Following Functions: i. C ( n, 1) ii. C ( n, 2) iii. C ( n, n/ 2) For even n ’s. b. What major implication For computing C ( ) do the answers to the questions in part (a) have? 6. ²ind the exact number oF additions made by the Following recursive algo- rithm based directly on Formulas (8.3) and (8.4). Algorithm BinomCoef ( ) if k =0 or k = n return 1 else return BinomCoef ( n 1 ,k 1)+ BinomCoef ( n 1 ) 7. Which oF the Following algorithms For computing a binomial coefficient is most efficient? 1
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a. Use the formula C ( n,k )= n ! k !( n k )! . b. Use the formula C ( n, k n ( n 1) ... ( n k +1) k ! . c. Apply recursively the formula C ( C ( n 1 ,k 1) + C ( n 1 ) for n>k> 0 , C ( n, 0) = C ( n,n )=1 . d. Apply the dynamic programming algorithm. 8. Prove that C ( C ( k ) for n k 0 and explain how this formula can be utilized in computing C ( ) . 9. Shortest path counting A chess rook can move horizontally or vertically to any square in the same row or in the same column of a chessboard. Find the number of shortest paths by which a rook can move from one corner of a chessboard to the diagonally opposite corner [Gar78], p.10 (a) by a dynamic programming algorithm. (b) by using elementary combinatorics. 10. ± World Series odds Consider two teams, A and B , playing a series of games until one of the teams wins n games. Assume that the probabil- ity of A winning a game is the same for each game and equal to p and the probability of A losing a game is q =1 p. (Hence, there are no ties.) Let P ( i,j ) be the probability of A winning the series if A needs i moregamestowintheseriesand B needs j more games to win the series. a. Set up a recurrence relation for P ( ) that can be used by a dy- namic programming algorithm.
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This note was uploaded on 04/28/2010 for the course CS CSE taught by Professor Drt during the Spring '10 term at Kaplan University.

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solu8 - This le contains the exercises hints and solutions...

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