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Data Structures by R.S. Chang, Dept. CSIE, NDHU1 Chapter 2 Algorithm Design Human Problems Result Input Data Structures Processing Output Data Structures Computer Algorithms

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Data Structures by R.S. Chang, Dept. CSIE, NDHU2 Chapter 2 Algorithm Design For a problem? What is an Optimal Solution? 用最少的 (CPU) 時間 ( 通常是指這點 ) 用最少的記憶體 Example: Given 4 numbers, sort it to nonincreasing order. Method 1: Sequential comparison 1. Find the largest (3 comparisons) 2. Find the second largest (2 comparisons) 3. Find the third largest (1 comparisons) 4. Find the fourth largest A total of 6 comparisons

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Data Structures by R.S. Chang, Dept. CSIE, NDHU3 Chapter 2 Algorithm Design For a problem? What is an Optimal Solution? 用最少的 (CPU) 時間 ( 通常是指這點 ) 用最少的記憶體 Example: Given 4 numbers, sort it to nonincreasing order. Method 2: Somewhat clever method a1 a2 a3 a4 a2a4 a2a3 a2a3 a2 a1a3 a3 or a1 (4 comparisons) (5 comparisons)

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Data Structures by R.S. Chang, Dept. CSIE, NDHU4 Chapter 2 Algorithm Design 2.1 Greedy Algorithms A greedy algorithm takes an action that seems the best at the given time, without consideration of future actions. Example: Coin changing problem Make change for any amount from $0.01 to $0.99 using the fewest number of coins. The available coins are $0.5, $0.25, $0.1, $0.05, and $0.01. $0.94=$0.5+$0.25+$0.1+$0.05+4*$0.01 A total of 8 coins Greedy algorithm works for U.S. coins. But not necessarily so for others. See Exercise 1 in Page 27.

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Data Structures by R.S. Chang, Dept. CSIE, NDHU5 Chapter 2 Algorithm Design 2.1 Greedy Algorithms Hill climbing concept Local optimumGlobal optimum

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Data Structures by R.S. Chang, Dept. CSIE, NDHU6 Chapter 2 Algorithm Design 2.2 Divide-and-Conquer Algorithms Example: Finding the minimum number in a list of numbers minimum(a,lower,upper) { if (upper-lower) == 1 return min(a[upper],a[lower]); else return min(minimum(a,lower,(lower+upper)/2), minimum(a,(lower+upper)/2+1,upper)); } Merge sort Quick sort

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Data Structures by R.S. Chang, Dept. CSIE, NDHU7 Chapter 2 Algorithm Design 2.2 Divide-and-Conquer Algorithms The closest pair problem d d For each point near the border, there can be at most six candidates for the closest neighbor across the border. Why?

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Data Structures by R.S. Chang, Dept. CSIE, NDHU8 Chapter 2 Algorithm Design 2.3 Dynamic Programming Algorithms Often a problem can be solved by divide-and- conquer, but it may turn out to be an inefficient algorithm because much work is duplicated when solving the subproblems. (or because the conquer (merge) step is too complicated)

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Data Structures by R.S. Chang, Dept. CSIE, NDHU9 Chapter 2 Algorithm Design 2.3 Dynamic Programming Algorithms The Fibonacci numbers Fibonacci(n) { if (n<2) return 1; else return Fibonacci(n-1)+Fibonacci(n-2); } F(5) F(3) F(4) F(1) F(2) F(3) F(1) F(2) Many repetitive calculations

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Data Structures by R.S. Chang, Dept. CSIE, NDHU10 Chapter 2 Algorithm Design 2.3 Dynamic Programming Algorithms The Fibonacci numbers Fibonacci(n) { int data[n]; data[0]=1; data[1]=1; for (j=2; j

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Data Structures by R.S. Chang, Dept. CSIE, NDHU11 Chapter 2 Algorithm Design 2.3 Dynamic Programming Algorithms The number of combinations

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Data Structures by R.S. Chang, Dept. CSIE, NDHU12 Chapter 2 Algorithm Design 2.3 Dynamic Programming Algorithms The number of combinations The Pascal’s triangle n r

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Data Structures by R.S. Chang, Dept. CSIE, NDHU13 Chapter 2 Algorithm Design 2.4 Backtracking Algorithms The tic-tac-toe game xx How can a computer play the game? Remember Deep Blue?

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Data Structures by R.S. Chang, Dept. CSIE, NDHU14 Chapter 2 Algorithm Design 2.4 Backtracking Algorithms The tic-tac-toe game x x (1,1)C (0,0)H (0,1)H (0,2)H (1,0)H... (0,0)C, (0,1)C, (1,0)C... (0,1)H, (1,0)H, …, (2,2)H (0,1)C, (1,0)C, (1,2)C, (2,0)C... : Computer x : Human

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Data Structures by R.S. Chang, Dept. CSIE, NDHU15 Chapter 2 Algorithm Design 2.4 Backtracking Algorithms 3 missionaries and 2 cannibals want to cross the river Condition: 1. A boat can take one or two (must include a missionary) 2. At any time, on either bank, the number of missionaries must not be less than the number of cannibals.

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