Abstract
In a metal grating manufacturing industry, the layout design of gratings is the most important activity of
the whole design process since it determines a large portion of manufacturing cost. However, due to the complexity of the problem in layout design phase, it is impossible to generate design alternatives and select the best design solution within a reasonable time period. In this paper, we apply genetic algorithms to search a near-optimal solution of the layout design problem, which is focused on the minimization of machining cost. We also employ heuristics to generate sub-design candidates for subproblems. The effectiveness of the proposed method is shown by experimental results.
