Method and system for conditioning of numerical algorithms for solving optimization problems within a genetic framework

A method for conditioning an algorithm to achieve optimum execution time, the method comprising:

• directing a master controller to provide an initial seed vector and an optimal pool size;
• directing a diversification module to generate a plurality of sibling vectors based on an input seed vector, wherein the initial seed vector is initially used as the input seed vector;
• instantiating a plurality of genetic modules using the optima pool size, wherein each genetic module is configured to perform a computational process and generate an off-spring vector based on a corresponding sibling vector received from the diversification module, and wherein the plurality of genetic modules perform their respective computational processes independently in a parallel manner;
• directing a generation depth manager to determine a generation depth for each of the plurality of genetic modules, wherein the generation depth is used by the corresponding genetic module to perform its computation process;
• directing a best fit evaluator to evaluate an objective function for the off-spring vector generated by each genetic module and generate an objective value;
• and
• directing a convergence manager to evaluate the objective value to determine if one or more terminal conditions associated with the objective function have been reached.