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The List Update or the List Access problem is a simple model used in the study of competitive analysis of online algorithms.Given a set of items in a list where the cost of accessing an item is proportional to its distance from the head of the list, e.g. a linked List, and a request sequence of accesses, the problem is to come up with a strategy of reordering the list so that the total cost of ...
Merge sort. In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order.The most frequently used orders are numerical order and lexicographical order, and either ascending or descending.
Note that the final result of an insertion sort is optimum, i.e., a correctly sorted list. For many problems, online algorithms cannot match the performance of offline algorithms. If the ratio between the performance of an online algorithm and an optimal offline algorithm is bounded, the online algorithm is called competitive. [1]
Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...
In computer science, selection sort is an in-place comparison sorting algorithm.It has a O(n 2) time complexity, which makes it inefficient on large lists, and generally performs worse than the similar insertion sort.
Internet search algorithms (1 C, 16 P) M. Metaheuristics (3 C, 15 P) P. Path planning (1 C, 4 P) S. String matching algorithms (1 C, 16 P) Pages in category "Search ...
Interpolation search is an algorithm for searching for a key in an array that has been ordered by numerical values assigned to the keys (key values).It was first described by W. W. Peterson in 1957. [1]
The shrink factor has a great effect on the efficiency of comb sort. Dobosiewicz suggested k = 4/3 = 1.333…, while Lacey and Box suggest 1.3 as an ideal shrink factor after empirical testing on over 200,000 random lists of length approximately 1000. A value too small slows the algorithm down by making unnecessarily many comparisons, whereas a ...