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Multilevel Coordinate Search (MCS) is an algorithm for bound constrained global optimization using function values only. To do so, the n-dimensional search space is represented by a set of non-intersecting hypercubes (boxes). The boxes are then iteratively split along an axis plane according to the value of the function at a representative point of the box and the box's size. These two splitting criteria combine to form a global search by splitting large boxes and a local search by splitting areas for which the function value is good. Additionally a local search combining a quadratic interpolant of the function and line searches can be used to augment performance of the algorithm. ==External links== * (Homepage of the algorithm ) * (Performance of the algorithm relative to others ) 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「MCS algorithm」の詳細全文を読む スポンサード リンク
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