A parallel solution for the 0–1 knapsack problem using firefly algorithm

Mohammad Hajarian, A. Shahbahrami, F. Hoseini
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引用次数: 8

Abstract

The knapsack problem is known as a NP-hard problem. There is a dynamic programming solution for this problem which is called the 0-1 knapsack. Firefly's innovative optimization algorithm is an algorithm, inspired by the behavior of fireflies flashing. This study represents a parallel solution for the 0-1 knapsack problem using firefly algorithm. Regarding parallel nature of most optimization algorithms they can be used successfully in a graphical processing unit (GPU). Since it is time consuming to test all the cases, when increasing the items and iterations, Compute Unified Device Architecture (CUDA) is used to implement the solution in a parallel way. The results of simulating the 0-1 knapsack problem using firefly algorithm on GPU hardware showed that the execution time of this method in a parallel way decreases with the increase of the population of fireflies and it is 320 times faster than serial solution and this rate is because of synchrony in execution of the blocks on GPU hardware.
用萤火虫算法并行求解0-1背包问题
背包问题被称为np困难问题。这个问题有一个动态规划的解决方案,叫做0-1背包。萤火虫的创新优化算法是一种算法,灵感来自萤火虫闪烁的行为。本文提出了一种利用萤火虫算法并行求解0-1背包问题的方法。考虑到大多数优化算法的并行性,它们可以在图形处理单元(GPU)中成功地使用。由于测试所有的情况是耗时的,当增加项目和迭代时,使用计算统一设备架构(CUDA)以并行的方式实现解决方案。在GPU硬件上用萤火虫算法模拟0-1背包问题的结果表明,该算法的并行执行时间随着萤火虫数量的增加而减少,比串行解决方案快320倍,这是由于GPU硬件上块的执行同步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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