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Satisficing is an alternative to optimization for cases where there are MULTIPLE and COMPETITIVE objectiveS in which one gives up the idea of obtaining a "best" solution. In this approach one sets lower bounds for the various objectives that, if attained, will be "good enough" and then seeks a solution that will exceed these bounds. The satisficer's philosophy is that in real-world problems there are too many uncertainties and conflicts in values for there to be any hope of obtaining a true optimization and that it is far more sensible to set out to do "well enough" (but better than has been done previously). (IIASA)
By evaluating all possible alternatives, the computation of an optimum strategy (see optimization theory) may not be feasible when the number of alternatives is very large (see combinatorial explosion). E.g., in chess, the number of available plays exceeds computational limits not just for humans (see bremermann's limit). A decision maker who settles for a less ambitious result and obtains the optimum he can compute under given time or resource constraints is said to satisfice. (Krippendorff)
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