| 摘要 |
Methods and apparatus for rapidly converging on a solution in a large ragged search space, such as NP-Complete space, where the solution is good but not necessarily the most optimum are provided First, Frequency and Neighborhood Tables are built (103) as seen in Figure 1 Next, vectors are instantiated (105) and a Fitness Engine evaluates the fitness of each vector (107) The N% of vectors with the lowest fitness are discarded (109) This is repeated until the criteria are met (111) After the criteria are met, the optional solver/optimizer may be used (113) If it is used (1 15), it is used until the criteria are met (117) Then the overcall criteria are checked, if they are not met, the method returns to the beginning (119) If the criteria are met, the vector with the best fitness is selected (121), and the optional optimization is performed on that vector (123)
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