The Direct insertion sort algorithm obtained in java an average run-time / array of 218.808273 microseconds, in C ++ an average run-time / array of 999.756718 microseconds and in C# an average run-time / array of 1817.122120 microseconds.
The Bubble Sort algorithm proved to be the most inefficient, obtaining in java an average run-time / array of 1329.853091 microseconds, in C ++ an average run-time / vector of 3339.091910 microseconds, and in C# an average run-time / vector of 5591.868977 microseconds.
The sort algorithm is employed to develop a merged list of pickups and deliveries, thereby setting priorities for vehicle routing.
The sort algorithm can be divided into unique phases as outlined below.
In this Section, we first introduce the performances of our BSPSO algorithm for the design of CNN template parameters, including the ability to get the template solution and the comparison results with GA, PSO BSPSO, and sort algorithm. Then, the performance of our VMMD model based on CNN algorithm is evaluated, such as the effects of VMMD model on migration lifecycle and the comparison results with other published existing algorithms.
Then, we optimize the template parameter by using GA, PSO, BSPSO, and sort algorithm. In order to analyze the superiority of the proposed algorithm quantitatively, we define an evaluation criteria formula as (19) by using the number of iterations and fitness variance
In Step3, the radix sort algorithm processes 8 elements per thread for the GTX 280 GPU, 16 for the GTX 480 GPU and 32 for the GTX 680 GPU, as we have called the GPU optimized parallel prefix sum function .
The solutions for optimizing the radix sort algorithmic function using the Compute Unified Device Architecture prove their efficiency when the function runs on GPUs from different generations and thus the function is useful and applicable in different scenarios and situations, in a variety of data processing applications that require the parallel radix sort algorithm.
Sort the array 15, 5, 12, 10, 20, 23, 18, 13, 3, 6, 7, and 19 by using the insertion sort algorithm
The insertion sort algorithm
has a complexity of O([n.sup.2]).
This paper is organized as follows: some basic concepts and definitions on knee point search and top-k sorting are presented in Section 2; Section 3 will design a knee point search algorithm, including basic idea, top-k sort algorithm, time complexity, parameter updating, cascading top-k sorting with minimized time complexity, the knee point search algorithm, and the solution of the optimization problem; Section 4 will introduce source detection of DNS DoS flooding attacks as an application example of the proposed algorithm; Section 5 will conclude this paper.
Therefore it is preferable to selectively sort first using the top-k sort algorithm and then search in each step.