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The decision-criterion in which a decision-maker selects an alternative that maximizes \(H\) (criterion of realism) \(= [a \times (\text{maximum in column})] + [(1 - a) \times (\text{minimum in column})]\) is called

This question was previously asked in
UGC NET 2016 Paper 2 Management Question Paper (22-Jan-2017)
The correct answer is

Hurwicz criterion

This is a decision-making-under-uncertainty problem, and the formula in the question is the signature of one particular criterion.

The criterion of realism recognises that a pure optimist and a pure pessimist both go too far, so it blends the best and the worst payoff of each alternative using a coefficient of optimism \(a\) that lies between 0 and 1. For each alternative it computes \(H = a \times (\text{maximum payoff}) + (1 - a) \times (\text{minimum payoff})\) and then chooses the alternative with the highest \(H\). This weighted blend of optimism and pessimism is exactly the Hurwicz criterion.

The other rules use different logic: the Laplace criterion assumes all states are equally likely and picks the alternative with the best simple average of payoffs; Wald's maximin looks only at each alternative's worst payoff and maximises that (pure pessimism); and the Bayesian (expected-value) criterion attaches probabilities to the states and maximises expected payoff.

Since the given formula weights only the maximum and minimum with \(a\) and \(1-a\), it identifies the Hurwicz rule.

Hence the criterion described is the Hurwicz criterion.

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