Heuristics are used in many disciplines because of the large number of experiments and calculations required to answer the underlying questions. TRIZ gathers and generalizes such heuristics and is perhaps the most powerful body of such heuristics. However past results or success, as in the performance of financial instruments or industrialists is no guarantee of future performance because the results are obtained in an uncontrolled or non-experimental environment. We provide methods that solve a broad class of problems whose solutions requires a large number of experiments or calculations or both. The methods we have developed achieve this result through the following.
1. Making optimization problems more tractable through dimension reduction or mapping into an easier problem.
2. Recognizing the most fundamental objective function arising from biology, that of self- preservation that drives all system evolution. Indeed, all system functions are special cases of this function.
3. Recognizing all value creation arises from relative increases of this objective function of self-preservation formulated as an entropy.
4. Time weighted by talent as the scarcest resource, and the most important constraint in all human activity.
5. Reducing search complexity of analysis, experiment, calculation by ensuring the system function is as close as possible to the desired function, the physical effect used is as close as possible to the system function, and the implementation objects are as close as possible to the system function.
Our framework shows why TRIZ heuristics have been successful and also shows how to build better heuristics.