Brute Force Optimizers

A brute force optimizer searches for the best possible solution by systematically testing all potential solutions, i.e., all definable combinations of rules, parameters, or both. Because every possible combination must be tested, brute force optimization can be very slow. Lack of speed becomes a serious issue as the number of combinations to be examined grows. Consequently, brute force optimization is subject to the law of “combinatorial explosion.” Just how slow is brute force optimization?
Consider a case where there are four parameters to optimize and whereeach parameter can take on any of 50 values. Brute force optimization would require that 504 (about 6 million) tests or simulations be conducted before the optimal parameter set could be determined: if one simulation was executed every 1.62 seconds (typical for Trade Station), the optimization process would take about 4 months to complete. This approach is not very practical, especially when many systems need to be tested and optimized, when there are many parameters, when the parameters can take on many values, or when you have a life.