This post talks about the fixed-length and variable-length encoding, uniquely decodable codes, prefix rules, and Huffman Tree construction. Huffman coding (also known as Huffman Encoding) is an algorithm for doing data compression, and it forms the basic idea behind file compression. Given a schedule containing the arrival and departure time of trains in a station, find the minimum number of platforms needed to avoid delay in any train’s arrival. Find minimum platforms needed to avoid delay in the train arrival Also, only a single task will be executed at a time. Assume that a task takes one unit of time to execute, and it can’t execute beyond its deadline. Given a set of tasks with deadlines and total profit earned on completing a task, find maximum profit earned by executing the tasks within the specified deadlines. This post will discuss a greedy algorithm for graph coloring and minimize the total number of colors used. Graph coloring (also called vertex coloring) is a way of coloring a graph’s vertices such that no two adjacent vertices share the same color. Given a set of activities, along with the starting and finishing time of each activity, find the maximum number of activities performed by a single person assuming that a person can only work on a single activity at a time. The coin of the highest value, less than the remaining change owed, is the local optimum.įollowing are commonly asked greedy algorithm problems in technical interviews: Activity Selection Problem These are the steps a human would take to emulate a greedy algorithm to represent 36 cents using only coins with values. The space complexity is O(1) as no additional memory is required.Figure: Greedy algorithms determine minimum number of coins to give while making change. The time complexity for the Fractional Knapsack Problem is O(NlogN) as it takes this much time to sort the unsorted list of items based on their calculated ratios. Total value obtained: 240.0 Time and Space Complexity Print("Total value obtained: "+str(totalValue))
Items.sort(key=lambda x: x.ratio, reverse = True) #Function to solve the Fractional Knapsack Problem #Initializing the Items class with data variables - weight and value
Select items with the highest ratio sequentially until the space in the collection allows.It is defined as the ration of value to weight of the given item. The Fractional Knapsack Problem makes use of the Greedy Algorithm in the following manner: Implementation of Fractional Knapsack Problem The space complexity is O(1) as no additional memory is required. The time complexity for the Activity Selection Problem is O(NlogN) as it takes this much time to sort the unsorted list of activities. #Function to solve the Activity Selection Problem #Initializing activities with start and finish times If so, select this activity and print it. For all the remaining activities, check whether the start time of the activity is greater or equal to the finish time ofthe previously selevted activity.
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