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- Exists a significant disadvantage to depending on algorithms?Q.8 How traditional algorithm differ from geneti algorithm ?Question 14 Sun Subject: ALGORITHM ANALYSIS AND DESIGN Explain in brief which one of the combinatorics (permutation/combination/subset) that is related to each of the following problems: 1. Travelling Saleman Problem (TSP) 2. Knapsack Problem 3. Job Assignment Problem
- a)(i). People often use recursive algorithms. Discuss the difference between direct recursion and indirect recursion. In which situations would a direct or indirect recursion be a better choice to use?(ii). Two Level 200 IT students, James and Morris, are discussing how to compare two algorithms for solving a given problem. James suggests that they should use the execution times of the algorithms as criterion; but Morris insists that they should use the number of statements the algorithms execute as criterion. (α)Explain the reasons why both criteria they are considering are not good for comparing algorithms. (β)Recommend an ideal solution/criterion that they should rather use for comparing algorithms. Give a practical example to illustrate your answer.QUESTION 1 Given the following time-complexity functions, f₁€ 0 (n³) f₂E0(4) which algorithm is faster for large inputs? a. Algorithm one is faster. Ob. Algorithm two is faster. Ⓒc. The two algorithms are equally fast. Od. We can not tell from the information given. QUESTION 2 Given the following time-complexity functions, f₁€ 0 (n³) f₂€0 (10n³) which algorithm is faster for large inputs? a. Algorithm one is faster. Ob. Algorithm two is faster. c. The two algorithms are equally fast. Od. We can not tell from the information given.1. Prepare an excel table to compute the runtime for four different algorithms for solving the same problem, for value of N ranging from N= 10 to 100 in steps of 10 and then determine the best and worst algorithm. The runtimes of the algorithms are given as below: T₁(N) = (1.2) T₂(N) = 3N³ + 200 T₂(N) = NIgN T4(N) = 100N Make sure to attach the excel spread sheet. Also, may be worth to plot the function on excel chart (line plot) and you can show the functions growth.
- Exercise 11: Using MATLAB Simulink to solve the following differential equations: r'y" – 2ry' + 4y = 0 Exercise 12: Using MATLAB Simulink to design a model to solve the system of linear equations: 6x, - 3x2 + 2x3 +x4 - Xg + x6 = 11 -3x1 - 7x2 + 0x3 + 4x4 – 2x5 +x6 = -5 4x1 - 3x2 + 6x3 - x, + 2x5 + x6 = 28 %3D 2x1 + 4x2 + 5x3 - 7x4 - 3x5 + 2x6 = -6 -x, + 5x2 – 4x3 + 0x, + 8x5 - 2x, = 25 %3D 3x, + 0x2 + 4xz + 2x4 + 5x5 - 6x, = -4Part 3: Comparison of Dijkstra and Bellman-Ford algorithms In part 3, please answer the following five questions in your PDF. Question 1: What is the time complexity of Dijkstra's algorithm? Please briefly describe the steps of the algorithm to justify the time complexity. Question 2: What is the time complexity of Bellman-Ford algorithm? Please briefly describe the steps of the algorithm to justify the time complexity. Question 3: How does the distance vector routing algorithm send routing packets? (To all nodes or only to neighbors) Question 4: How does the link state routing algorithm send routing packets? (To all nodes or only to neighbors) Question 5: When a link cost changes, which steps does the distance vector algorithm take?item 1 2 3 4 4 3 weight 2 value 10 20 5 Solve the knapsack problem for three repetition of the main loop of the genetic algorithm. Capacity = 25kg 5 сл 5 5 7 6 15 10 20 7 The number of primary chromosomes=5 Stop condition...three repetition of the main loop 12 18 By hand calculation not by software
- Four different algorithms that perform the same business process are called B, C, D and H. (1) the total number of operations performed using algorithm B is 64n. (2) the total number of operations performed using the C algorithm is 16n^2 (3) the total number of operations (operations) performed using the D algorithm is "n". Detecting problem size n0 where 64n is better than 16n^2 for n > n0please.For this code answer the following ALGORITHM Mystery (n)S ← 0for i ← 1 to n doS ← S + i*iReturn S (a) What does the algorithm computes?(b) Write the running time for each line, and derive the exact time?(c) What is the basic operation?(d) What is the efficiency class of this algorithm?(e) Can we do better algorithm?2. Following are the various algorithms time complexities expressions. Find the dominant terms and specify the Big-Oh complexity of each algorithm. [10 x 4] S. No. Dominant term(s) O(. . ) Expression 75 + 0.001n3 + 0.025n + (1000)4 500n + 100n3 + 50n³ log10 n (10n2.6)4 + 0.3n + 5n10.3 + 2.5 ·n².75 150n4 + n² log2 n + (n(log2 n))“ 3 log10 n + log, log, n 100n3 + 0.01n² + 200(log2 n)ª 1.3 1. 2. 3. 4. 5. 6. 7. n3 + 0.01n + 100n2 + 5n3 2n0.5 + n0.35 + 0.5n0.25 0.01n² log2 n + n(log, n) 50n³ log3 n + n³ log3 n + 100n“ 8. 9. 10.