We have discussed greedy algorithm during lectures. A greedy algorithm is an algorithm that recursively construct a set of objects from the smallest possible constituent parts. At each one of the iterations, the algorithm takes the best that it can get right now, without regards for future consequences. The algorithm hopes that by choosing a local optimum at each one of the iterations, it can end up at a global optimum. In this assignment, you will write a program to schedule final examination for the examination department so that no student has two examinations at the same time. The goal of this assignment is to expose you to the implementation of greedy algorithms that solves a problem with constraints. You will use a greedy algorithm to determine an assignment of classes to examination slots (schedules) such that: 1. No student, enrolled in two subjects, is assigned to the same examination slot (schedule.) 2. Any attempt to combine two slots into one would violate rule 1. Input to the program will consist of the name of a data file. This file will contain the following data: The number of students enrolled in the current semester Repeated rows of the following: o Name of the student and the total number of subjects enrolled o The subject code the student is enrolled in. A sample of an input file is as follow: 3 Melissa, 4 CSCI203 CSCI235 CSCI222 CSCI205 Bernard, 4 CSCI213 CSCI222 CSCI204 CSCI203 Terrence, 4 CSCI212 CSCI203 CSCI235 CSCI213

Computer science

Personal project Q5. This question is concerned with the design and analysis of recursive algorithms. You are given a problem statement as shown below. This problem is concerned with performing calculations on a sequence A of real numbers. Whilst this could be done using a conventional loop-based approach, your answer must be developed using a recursive algorithm. No marks will be given if your answer uses loops. FindAverageAndProduct(a1, ...., an) such that n > 1 Input: A sequence of real values A = (a1, ...., an) Output:, A 2-tuple (average, product) containing the average (average) of all the values and the product (product) of all the values of the elements in A. Your recursive algorithm should use a single recursive structure to find the average and product values, and should not use two separate instances of a recursive design. You should not employ any global variables. (a) Produce a pseudo code design for a recursive algorithm to solve this problem. (b) Draw a call-stack…

Personal project Q5. This question is concerned with the design and analysis of recursive algorithms. You are given a problem statement as shown below. This problem is concerned with performing calculations on a sequence ? of real numbers. Whilst this could be done using a conventional loop-based approach, your answer must be developed using a recursive algorithm. No marks will be given if your answer uses loops. FindAverageAndProduct(a1, ...., an) such that n > 1 Input: A sequence of real values A = (a1, ..., an) Output:, A 2-tuple (average, product) containing the average (average) of all the values and the product (product) of all the values of the elements in A. Your recursive algorithm should use a single recursive structure to find the average and product values, and should not use two separate instances of a recursive design. You should not employ any global variables. (a) Produce a pseudo code design for a recursive algorithm to solve this problem.   (b) Draw a call-stack…

We have discussed greedy algorithm during lectures. A greedy algorithm is an algorithm that recursively construct a set of objects from the smallest possible constituent parts. At each one of the iterations, the algorithm takes the best that it can get right now, without regards for future consequences. The algorithm hopes that by choosing a local optimum at each one of the iterations, it can end up at a global optimum. In this assignment, you will write a program to schedule final examination for the examination department so that no student has two examinations at the same time. The goal of this assignment is to expose you to the implementation of greedy algorithms that solves a problem with constraints. You will use a greedy algorithm to determine an assignment of classes to examination slots (schedules) such that: 1. No student, enrolled in two subjects, is assigned to the same examination slot (schedule.) 2. Anyattempttocombinetwoslotsintoonewouldviolaterule1. Input to the program…

Matlab Question

The following recursive definition of a set S over {a, b, c, d}. Basis: "", a, b, c E S. Recursive Step: If ax E S, then bax ES and cax E S. If bx € S, then cbx € S. If cx = S, then bax ES and bcx = S. If dx E S, then ddx E S. Closure: SE S only if it is a, b or c or it can be obtained from a, b or c using finitely many operations of the Recursive Step. a) What recursive step can be removed from the above definition and why? b) Derive from the definition of S that bcbc S. c) Explain why baa & S.

The following code is implementing a Treasure map use the A* algorithm to find the shortest path between two points in a map.  It appears that the initial compare looks at the f_cost and decides that we are at the point in the map and exits the routine and prints only the starting point.  I'm not sure how to fix it, any help would get appreciated.  Example of the output from the following Python program: start place = (0, 0) Treasure location: (29, 86)  Path to treasure:(0, 0) Python Code: import heapqimport random class Tile:    def __init__(self, x, y):        self.x = x        self.y = y        self.is_obstacle = False        self.g_cost = 0        self.h_cost = 0        self.f_cost = 0        self.parent = None     # Define comparison methods for Tile objects based on their f_cost    def __lt__(self, other):        return self.f_cost < other.f_cost     def __eq__(self, other):        return self.f_cost == other.f_cost class Map:    def __init__(self, width, height):…

1. A certain computer algorithm executes four times as many operations when it is run with an input of size n as when it is run with an input of size n – 1. Here, n > 1 is an integer. When the algorithm is run with an input of size 1, it executes 12 operations. How many operations does the algorithm execute when it is run with an input of size 5? How many operations does the algorithm execute when it is run with an input of size n?

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