PARALLEL EVOLUTIONARY SOLUTION METHOD FOR SEARCH SPACE SEGMENTATION

Abstract: the invention discloses a parallel evolutionary solution method for search space segmentation, comprising: s, randomly generating solution schemes via a search space sampling and segmentation module, calculating fitness values by combining initial sample schemes with an optimization objective function, statistically screening sample schemes, determining the dimension direction k of the segmented search space, and dividing the search space into subspaces; s, executing a global search algorithm in the segmented subspaces to obtain a global initial solution scheme; s, using the global initial solution scheme as a starting point, obtaining a precise solution scheme via a local search algorithm. this method employs evolutionary sampling of the search space, deriving fitness terrain analysis results, and guiding the division direction and step size of the search space. multiple search subspaces are segmented to enable parallel search for subsequent evolutionary calculations.

Inventor(s): Mingcheng ZUO, Dunwei GONG

CPC Classification: G06F17/11 (for solving equations {, e.g. nonlinear equations, general mathematical optimization problems (optimization specially adapted for a specific administrative, business or logistic context )})

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