A possible decision criterion in optimization under uncertainty is the minimax regret criterion. In this decision criterion, the decision maker first calculates the maximum regret for each feasible decision and then selects a decision that has the minimum maximum regret. Here, regret is the difference between the outcomes of a decision made and the best decision after some outcome scenario is realized. For example, if the decision you make and the outcome you observe lead to a $50 payoff, and if the highest payoff in this outcome's column is $80, then your regret is $30. You regret looking back and seeing how much more you could have made, if only you had made a different decision. Apply this criterion to the following example and choose the best decision under this criterion: A company is considering to make a bid on a contract. No company knows what the other competitors are bidding, and the low bid wins the contract. The company estimates that it will cost $2000 to prepare a bid and $80,000 to complete the project if it wins the contract. In addition, the company believes that there is a 30% chance that there will be no competing bids, and if there is any competition, the possible low bids from the competition the associated probabilities are as follows: Low Bid Less than $115,000 Between $115,000 and $120,000 Between $120,000 and $125,000 Greater than $125,000 Probability 0.2 0.4 0.3 0.1 What should the company bid to minimize the maximum regret