Final answer:
Optimization does not necessarily assume exact input data values, as various forms cater to uncertainty. The statement is false because optimization can include methods like stochastic or robust optimization, designed to deal with uncertain or variable data.
Step-by-step explanation:
Optimization does not implicitly assume that we know all of the values of the input data exactly; therefore, the statement is false. In many optimization problems, there is an acknowledgment of uncertainty or variability in input data. This is why various forms of optimization, such as stochastic optimization or robust optimization, exist. Stochastic optimization accounts for uncertainty by optimizing expected performance, while robust optimization seeks solutions that are effective under a range of possible input values. The standard form of optimization assumes known and precisely defined parameters, but real-world applications often require these more sophisticated approaches to handle data uncertainty and variability.
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