Although additive manufacturing (AM) has big potentials to print quite complex structures, the design and printing preparation is still quite chanllenge, especilly for complex fine porous structures. To avoid the accuracy loss along the AM processing chain, this research proposes to develop a new generative design for AM method, toolpath-based layer construction method. This method will use the physical deposition profile to define cellular layer patterns, and then apply knowledge based method with evolutionary algorithms to construct toolpath layers but not 2D contours slices to directly build a full processing model for printing. Advanced numerical simulation methods and printing quality evaluation and control methods will be developed to suport the decision making on design and processing compensation to ensure that the generated and identified optimal design solution is qualified. Industrial case studies will be conducted to demonstrate and promote the application. In the end, a design and printing preparation tool prototype will be developed on Rhino Grasshopper platform as an open source software tool to attract more public contributors to further develop and promote the new layer construction design method in AM.