CAJ | 학술논문

提出了一种多元化群智能优化算法—多元优化算法。多元优化算法充分利用了现代计算机多核处理器，大内存的特点，通过多元化的搜索个体（元）对优化问题解空间进行搜索，并对历史信息进行选择记忆。该算法因搜索群具有分工不同的多元化特点而得名。搜索元按照职责不同而分为全局元和局部元，全局元负责在整个搜索空间进行全局搜索并找到潜在解区域，局部元负责在各个潜在解区间进行局部搜索以期望找到该区域更好的解。本文从理论上证明了该算法的可达性。基于标准函数的对比实验也验证了该方法在可达性方面优于其他几个参与比较的算法。
제출료일충다원화군지능우화산법—다원우화산법。다원우화산법충분이용료현대계산궤다핵처리기，대내존적특점，통과다원화적수색개체（원）대우화문제해공간진행수색，병대역사신식진행선택기억。해산법인수색군구유분공불동적다원화특점이득명。수색원안조직책불동이분위전국원화국부원，전국원부책재정개수색공간진행전국수색병조도잠재해구역，국부원부책재각개잠재해구간진행국부수색이기망조도해구역경호적해。본문종이론상증명료해산법적가체성。기우표준함수적대비실험야험증료해방법재가체성방면우우기타궤개삼여비교적산법。
A multivariant optimization algorithm (MOA)is proposed.The proposed method makes full use of the multi-core processors and the large memory of modern computers.Multivariant searchers (atoms)ex-plore the solution space and remember the historical information selectively.The MOA gets its name from the multivariant characters of multiple searchers.Atoms are divided into global atoms and local atoms according to variant responsibilities.Global atoms explore the whole solution space to discover potential areas.Local atoms exploit potential areas for a local refinement.Theoretically,the MOA is proved to be accessible to the global optimal solution.Experiments based on benchmark functions show that the MOA has competitive performance compared with other methods in terms of accessibility.