The paper deals with the investigation of the critical non-linear factors and NP-hard problems of real-life decision-making processes. When using non-linear utility/objective functions to represent the value of various options in the search space or when NP-hard problems arise, often soft computing techniques must be applied for optimization. Many times significant uncertainty must be handled as well, so the use of fuzzy numbers can be an efficient method to cope with ambiguity and lack of information. The fuzzy extensions for heuristic based optimizing algorithms often face the problem of an increased number of calculations required to find the solutions. Appropriate representation of the fuzzy power function for non-linear cases is to be used so that it can keep the required computation time and resources at a reasonable level. © 2012 ICIC International.