计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2015年
7期
1927-1931,1937
,共6页
徐以坤%余洋%米增强%赵彤
徐以坤%餘洋%米增彊%趙彤
서이곤%여양%미증강%조동
生物地理学优化%微分进化%约束优化%混合算法%全局优化
生物地理學優化%微分進化%約束優化%混閤算法%全跼優化
생물지이학우화%미분진화%약속우화%혼합산법%전국우화
BBO%DE%constrained optimization%hybrid algorithm%global optimization
针对生物地理学优化算法(biogeography based optimization ,BBO)容易陷入局部最优解的缺点,提出一种基于微分进化(differential evolution ,DE)改进BBO算法的混合生物地理学(BBO‐DE)优化算法。通过有机结合BBO算法的利用能力和DE算法的搜索能力,实现利用能力与搜索能力的平衡;引入基于可行性的约束处理机制,解决传统BBO算法无法求解约束优化的问题。通过选定的8个标准测试函数对改进算法进行仿真测试,测试结果验证了改进算法的可行性和有效性,与基本BBO和DE算法相比,其在最终解的质量和收敛速度上具有明显优势。
針對生物地理學優化算法(biogeography based optimization ,BBO)容易陷入跼部最優解的缺點,提齣一種基于微分進化(differential evolution ,DE)改進BBO算法的混閤生物地理學(BBO‐DE)優化算法。通過有機結閤BBO算法的利用能力和DE算法的搜索能力,實現利用能力與搜索能力的平衡;引入基于可行性的約束處理機製,解決傳統BBO算法無法求解約束優化的問題。通過選定的8箇標準測試函數對改進算法進行倣真測試,測試結果驗證瞭改進算法的可行性和有效性,與基本BBO和DE算法相比,其在最終解的質量和收斂速度上具有明顯優勢。
침대생물지이학우화산법(biogeography based optimization ,BBO)용역함입국부최우해적결점,제출일충기우미분진화(differential evolution ,DE)개진BBO산법적혼합생물지이학(BBO‐DE)우화산법。통과유궤결합BBO산법적이용능력화DE산법적수색능력,실현이용능력여수색능력적평형;인입기우가행성적약속처리궤제,해결전통BBO산법무법구해약속우화적문제。통과선정적8개표준측시함수대개진산법진행방진측시,측시결과험증료개진산법적가행성화유효성,여기본BBO화DE산법상비,기재최종해적질량화수렴속도상구유명현우세。
Basic biogeography based optimization (BBO) can be easily trapped into local optima .To modify the defect ,a hybrid biogeography based optimization with differential evolution (BBO‐DE) was proposed ,which combined the exploitation ability of BBO and the exploration ability of differential evolution (DE) reasonably to balance the exploitation ability and exploration abili‐ty .In addition ,feasibility‐based constraint handling mechanism was introduced into BBO‐DE ,which extended traditional BBO to solve constrained optimization problem .The proposed BBO‐DE was performed on eight selected benchmark functions .Simula‐tion results demonstrate that it is a feasible and effective method for constrained optimization .With respect to basic BBO and DE , BBO‐DE has distinct superiority in terms of the quality of final solutions and the convergence speed .