Explain the job sequencing with deadline algorithm and also find the solution for the instance n = 7 , (P 1, P2 ,....P7 )=(3, 5, 20, 18, 1, 6, 30) and (D₁, D₂, ..... D7) = (1, 3, 4, 3, 2, 1, 2
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Computer's science
Algorithms
Explain the job sequencing with deadline
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- with n=6 and A=(3,5,4,1,3,2). Draw the corresponding walkthrough as shownApply algorithm 4.3.3 in P.158 with n=6 and A=(3,5,4,1,3,2). Draw the corresponding walkthrough as shown in P.158.Algorithm design with sorting. Each of n users spends some time on a social media site. For each i = 1, . . . , n, user i enters the site at time ai and leaves at time bi ≥ ai. You are interested in the question: how many distinct pairs of users are ever on the site at the same time? (Here, the pair (i, j) is the same as the pair (j, i)).Example: Suppose there are 5 users with the following entering and leaving times: Then, the number of distinct pairs of users who are on the site at the same time is five: these pairs are (1, 2), (1, 3), (2, 3), (4, 6), (5, 6). (Drawing the intervals on a number line may make this easier to see).(a) Given input (a1 , b1),(a2 , b2), . . . ,(an, bn) as above in no particular order (i.e., not sorted in any way), describe a straightforward algorithm that takes Θ(n2)-time to compute the number of pairs of users who are ever on the site at the same time, and explain why it takes Θ(n2)-time. [We are expecting pseudocode and a brief justification for its…
- A graph is a collection of vertices and edges G(V, E). A weighted graph has weights (numbers, etc.) on every edge. A multigraph can have more than one edges between any vertices. Explain why a person should use a weighted graph instead of a multigraph. Give examples. An adjacency matrix might be a better choice for speeding up a program, however, it consumes huge memory for large graphs. How this situation can be improved? What programming constructs better suit graph representation? Explain with exampleCreate a simple matching algorithm for a round robin competition. in which the number of participants is n (1 n) and the round index is r (0 r 2 (n 1)/2.out: When i = 0,..., n/2 1, a sequence R of n player indices signaling the match pairings between players R2i and R2i+1; if n is odd, Rn1 denoting the resting playerImplement Queens algorithm: pre-cond: C = 1, c1, 2, c2, ... , r, cr places the jth queen in the jth row and the cjth column. The remaining rows have no queen.post-cond: Returned if possible is a placement optSol of the n queens consistent with this initial placement of the first r queens. A placement is legal if no two queens can capture each other. Whether this is possible is flagged with optCost equal to one or zero.
- The Python implementation updates the cost of reaching from the start vertex to each of the explored vertexes. In addition, when it decides on a route, A* considers the shortest path from the start to the target, passing by the current vertex, because it sums the estimate from the heuristic with the cost of the path computed to the current vertex. This process allows the algorithm to perform more computations than BFS when the heuristic is a proper estimate and to determine the best path possible.Adam begins to master programming. The main undertaking is drawing a fox! Notwithstanding, that ends up being excessively hard for a novice, so she chooses to draw a snake all things being equal. A snake is an example on a n by m table. Mean c-th cell of r-th column as (r, c). The tail of the snake is situated at (1, 1), then, at that point, it's body reaches out to (1, m), then, at that point, goes down 2 lines to (3, m), then, at that point, goes left to (3, 1, etc. Your undertaking is to draw this snake for Adam: the unfilled cells ought to be addressed as speck characters ('.') and the snake cells ought to be loaded up with number signs ('#'). Consider test tests to comprehend the snake design for the programming concepts.Computer science. Correct answer will be upvoted else downvoted. Think about a n by n chessboard. Its columns are numbered from 1 to n from the top to the base. Its sections are numbered from 1 to n from the passed on to one side. A cell on a convergence of x-th line and y-th section is indicated (x,y). The fundamental corner to corner of the chessboard is cells (x,x) for all 1≤x≤n. A stage of {1,2,3,… ,n} is composed on the fundamental slanting of the chessboard. There is actually one number composed on every one of the cells. The issue is to segment the cells under and on the principle askew (there are by and large 1+2+… +n such cells) into n associated areas fulfilling the accompanying imperatives: Each district ought to be associated. That implies that we can move from any cell of a locale to some other cell of a similar area visiting just cells of a similar district and moving from a cell to a neighboring cell. The x-th area ought to contain cell on the fundamental…
- You are the TA for the FCP course in environment engineering. You are given the midsem and endsem marks for the N Students in the course. A student P is said to dominate a student Q, if the midsem and endsem marks of P are both greater than the respective midsem and endsem marks of Q. Design an efficient algorithm for finding all the students that are not dominated by any other student in the class. Analyse the time complexity as wellAnswer the given question with a proper explanation and step-by-step solution. You are asked to pick up a project on building highways to connect all cities in the country. The cost of building a highway between two cites i and j is c(i, j) > 0. If you were in charge from the beginning, this would have been a minimum spanning tree problem and could be solve easily with the algorithms covered in class. Since you pick it up halfway, however, some suboptimal choices have already been made by your predecessor. In other words, highways were already built between some pairs of cities. Design an algorithm to find a cost minimizing set of highways to built subject to the choices already made. Do not copy others.Write a function find_equivalent_matchings that takes a matching and returns all matchings with the same pattern (including the original one). Using this function, draw all matchings equivalent to {(0, 7), (1, 4), (2, 3), (5, 6)}. You might find it helpful to generate all permutations of a list using itertools.permutation (imported above) as in the following code template. perms=permutations (list_of_items) for p in perms: