机床与液压
機床與液壓
궤상여액압
MACHINE TOOL & HYDRAULICS
2014年
18期
96-102
,共7页
萤火虫算法%模拟退火策略%退火方式%回火策略%Benchmark
螢火蟲算法%模擬退火策略%退火方式%迴火策略%Benchmark
형화충산법%모의퇴화책략%퇴화방식%회화책략%Benchmark
Glowworm swarm optimization (GSO )%Simulated annealing strategy%Annealing method%Temper strategy%Benchmark
萤火虫算法是群智能领域近年出现的一个新的研究方向，该算法虽已在复杂函数优化方面取得了成功，但也存在着易于陷入局部最优且进化后期收敛速度慢等问题，而模拟退火机制具有很强的全局搜索能力，结合两者的优缺点，提出一种融合模拟退火策略的萤火虫优化算法。改进后的算法在萤火虫算法全局搜索过程中融入模拟退火搜索机制，在局部搜索过程中采用了回火策略，改善寻优精度，改进了萤火虫算法的全局搜索性能和局部搜索性能。仿真实验结果表明：改进后的算法在收敛速度和解的精度方面有了显著地提高，证明了算法改进的可行性和有效性。
螢火蟲算法是群智能領域近年齣現的一箇新的研究方嚮，該算法雖已在複雜函數優化方麵取得瞭成功，但也存在著易于陷入跼部最優且進化後期收斂速度慢等問題，而模擬退火機製具有很彊的全跼搜索能力，結閤兩者的優缺點，提齣一種融閤模擬退火策略的螢火蟲優化算法。改進後的算法在螢火蟲算法全跼搜索過程中融入模擬退火搜索機製，在跼部搜索過程中採用瞭迴火策略，改善尋優精度，改進瞭螢火蟲算法的全跼搜索性能和跼部搜索性能。倣真實驗結果錶明：改進後的算法在收斂速度和解的精度方麵有瞭顯著地提高，證明瞭算法改進的可行性和有效性。
형화충산법시군지능영역근년출현적일개신적연구방향，해산법수이재복잡함수우화방면취득료성공，단야존재착역우함입국부최우차진화후기수렴속도만등문제，이모의퇴화궤제구유흔강적전국수색능력，결합량자적우결점，제출일충융합모의퇴화책략적형화충우화산법。개진후적산법재형화충산법전국수색과정중융입모의퇴화수색궤제，재국부수색과정중채용료회화책략，개선심우정도，개진료형화충산법적전국수색성능화국부수색성능。방진실험결과표명：개진후적산법재수렴속도화해적정도방면유료현저지제고，증명료산법개진적가행성화유효성。
Artificial glowworm swarm optimization algorithm is a new research orientation in the field of swarm intel igence recently.The algorithm has achieved success in the complex function optimization,but it is easy to fal into local optimum,and has the low speed of convergence in the later period and so on.Simulated annealing algorithm has excel ent global search ability.Combi-ning their advantages,an improved glowworm swarm optimization algorithm was proposed based on simulated annealing strategy.The simulated annealing strategy was integrated into the process of glowworm swarm optimization algorithm.And the temper strategy was integrated into the local search process of hybrid algorithm to improve search precision.Overal performance of the Glowworm swarm optimization was improved.Simulation results show that the hybrid algo-rithm increases the accuracy of solution and the speed of convergence significantly,and is a fea-sible and effective method.
