萤火虫优化算法的fpga硬件实现

H. Sadeeq, A. Abdulazeez
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引用次数: 15

摘要

人工元启发式算法的核心任务是通过融合随机性和其他模拟规则来模拟昆虫群居现象,如鸟群和昆虫群体。这种算法是最有效和最强大的技术,用于解决各种复杂的现实世界的优化问题。萤火虫算法的灵感来源于自然界萤火虫的交配和闪烁行为或生物发光交流现象,属于自然界的元启发式算法。本文提出了萤火虫算法的硬件结构设计。萤火虫算法与所有的元启发式算法一样是顺序执行的,这是由于算法的性质。因此,提出了基于有限状态机(FSM)系统的算法串行硬件结构设计。硬件设计结构实现映射到fpga (SPARTAN 3XS1600)器件上。对Firefly算法的硬件实现和软件实现(采用c++编程语言)进行了数值比较。这些结果表明,硬件实现的执行速度比软件实现快461倍。实际上,使用所提出的硬件设计结构可以快速减少寻找最优解决方案所需的执行时间。
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Hardware Implementation of Firefly Optimization Algorithm Using FPGAs
Mimicking natural phenomenon of social insects, such as bird flocks and insect colonies by merging randomness facility and some other simulation rules, are the core tasks of the artificial meta-heuristic algorithms. Such algorithms are the most efficient and powerful techniques used to solve various complicated real-world optimization problems. Firefly algorithm, which belongs to nature meta-heuristics algorithms, is inspired by mating and flashing behavior or the phenomenon of bioluminescent communication of fireflies in the nature. In this paper, a hardware structure design for firefly algorithm has been proposed. Firefly algorithm is executing sequentially as all meta-heuristic algorithms, due to the nature of the algorithm. Therefore, sequential hardware structure design for the algorithm using Finite State Machine (FSM) system has been proposed. The hardware design structure implementation is mapped into a FPGAs (SPARTAN 3XS1600) device. Numerical results of the comparison between the hardware and the software (using C++ programming language) implementation of Firefly algorithm were obtained. These results indicate that the hardware implementation is executed 461 times faster than the software implementation. Indeed, the required execution time for finding the optimal solution can be reduced rapidly using the proposed hardware design structure.
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