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CSCI 6212 Design and Analysis of Algorithms Dynamic Programming Dr. Juman Byun The George Washington University Please drop this course if you have not taken the following prerequisite. Sometimes enthusiasm alone is not enough. CSci 1311: Discrete Structures I (3) CSci 1112: Algorithms and Data Structures (3)

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Example: Rod Cutting n=4

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Example: Rod Cutting length iprice p i 1$1 2$5 3$8 4 $9 $10 5$10 6$17 7 8$20 9$24 10$30 Maximum Revenue, r 4 ? n=4

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r n when n=4 ? ip[i] 1$1 2$5 3$8 4 $9 $10 5$10 6$17 7 8$20 9$24 10$30 $9$1$8$5 $8$1 $5$1$5$1$5$1 $10

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Notation $5 $10 rod into 2 pieces4-inch Decomposition: 4 = 2 + 2 r 4 = $5 + $5 Maximum Revenue:

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Notation rnrn rnrn rod into k piecesn-inch Decomposition: n = i 1 + i 2 + … + i k Maximum Revenue:

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General Procedure to Find Optimal Rod Cutting Uncut Rod of length npnpn r 1 + r n-1 r 2 + r n-2 r n-2 + r 2 r n-1 + r 1 CutRevenue Pick the largest

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General Procedure to Find Optimal Rod Cutting

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Recursive Top-Down Cut-Rod(p,n) 1.if n == 0 2.return 0 3.q = -∞ 4.for i = 1 to n 5.q = max(q,p[i] + Cut-Rod(p, n - i ) ) 6.return q

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vs Divide-and-conquer Similarity to divide problems into subproblems Difference subproblems overlap

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Can we do better ?

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Momoized-Cut-Rod Memoized-Cut-Rod(p,n) 1.let r[0..n] be a new array 2.for i = 0 to n 3.r[i] = -∞ 4.return Memoized-Cut-Rod-Aux(p,n,r)

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Momoized-Cut-Rod-Aux Momoized-Cut-Rod-Aux(p,n,r) 1.if r[n] >= 0 2.return r[n] 3.if n == 0 4.q = 0 5.else q = -∞ 6.for i = 1 to n 7.q = max(q,p[i]+Memoized-Cut-Rod-Aux(p,n-i,r)) 8.r[n] = q 9.return q

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Bottom-Up-Cut-Rod Bottom-Up-Cut-Rod(p,n) 1.let r[0..n] be a new array 2.r[0] = 0 3.for j = 1 to n 4.q = -∞ 5.for i = 1 to j 6.q = max(q, p[i] + r[j-i]) 7.r[j] = q 8.return r[n]

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Running Time

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Extended-Bottom-Up-Cut- Rod Extended-Bottom-Up-Cut-Rod(p,n) 1.let r[0..n] and s[0..n] be new arrays 2.r[0] = 0 3.for j = 1 to n 4.q = -∞ 5.for i = 1 to j 6.if q < p[i] + r[j-i] 7.q = p[i] + r[j-i] 8.s[j] = i 9.r[j] = q 10.return r and s

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Lecture 30 CSE 331 Nov 10, 2010. Online Office Hours

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