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Bubble sort is a basic algorithm for arranging a string of numbers or other elements in the correct order. The method works by examining each set of adjacent elements in the string, from left to right, switching their positions if they are out of order. The algorithm then repeats this process until it can run through the entire string and find no two elements that need to be swapped. Know More
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In selection sort, the first element in the list is selected and it is compared repeatedly with all the remaining elements in the list. If any element is smaller than the selected element (for Ascending order), then both are swapped so that first position is filled with the smallest element in the sorted order. Next, we select the element at a second position in the list and it is compared with all the remaining elements in the list. If any element is smaller than the selected element, then both are swapped. This procedure is repeated until the entire list is sorted. Know More
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In insertion sort, an array is virtually split into a sorted and an unsorted part. Values from the unsorted part are picked and placed at the correct position in the sorted part. Each element in the array is checked with the previous elements, resulting in a growing sorted output list. With each iteration, the sorting algorithm removes one element at a time and finds the appropriate location within the sorted array and inserts it there. The iteration continues until the whole list is sorted. Know More
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Quicksort algorithm follows divide-and-conquer method. In this case a pivot point is chosen from the array.Then the array is reordered so that all values smaller than the pivot are moved before it and all values larger than the pivot are moved after it, with values equaling the pivot going either way. When this is done, the pivot move to it's final position. The step is repeated recursively for each subarray of smaller values as well as done separately for the subarray with greater values. Know More
From the tree root it explores all of the neighbor nodes at the present depth prior to moving on to the nodes at next depth level.
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It starts at the tree root and explores as far as possible along each branch in it's descendant before backtracking.
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For a given source node in the graph, the algorithm finds the shortest path between that node and every other.
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It is an informed search algorithm, as it uses information about path cost and also uses heuristics to find the solution.
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