Additive manufacturing model attitude multi-objective optimization method and equipment based on penalty function constraint

Abstract

The invention discloses a penalty function constraint-based additive manufacturing model attitude multi-objective optimization method and equipment. The method comprises the following steps of: (1) establishing a multi-objective optimization model which takes a part model attitude as an optimization parameter and optimization objectives at least comprise printing time, support quantity and volume error; (2) generating a construction space size; (3) initializing a candidate part model attitude population; (4) evolution is carried out through a population evolution mechanism to form offspring candidate part model postures; (5) rotating the part model under the posture of each parent candidate part model and each child candidate part model, and calculating the size of a bounding box of the rotated part model; (6) determining a penalty value according to the size of the bounding box; (7) updating the population according to the penalty value and the fitness; and (8) returning to execute the step (4) until iteration is ended, and selecting a feasible solution with a penalty value of 0 from the population to form an optimal attitude set. The method considers construction of spatial constraints and realizes multi-objective optimization, and the result is more accurate.

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