i$.$ Consider a bi$-$objective optimization problem. For one of the objective functions, there are alternative optima. Each of these alternative optimum solutions will be a Pareto efficient solution for the bi$-$objective model. True or False? True False

ii$.$ Which of the following is a supervised method to reduce a multi$-$objective optimization model.

$[1]$ Minimizing the maximum deviation

$[2]$ Minimizing the distance to the ideal point

$[3]$ Optimizing a weighted average of the objective function using specific weights

iii. Which of the following is true about weighted goal programming?

$[1]$ It sequentially optimizes goals while maintaining the achieved levels of prior goals.

$[2]$ It minimizes the maximum of the deviations from individual goals.

$[3]$ It assigns penalties to deviations from the goals and minimizes the total penalty.

iv$.$ Which of the following best describes the preemptive goal programming?

$[1]$ It sequentially optimizes goals while maintaining the achieved levels of prior goals.

$[2]$ It minimizes the maximum of the deviations from individual goals.

$[3]$ It assigns penalties to deviations from the goals and minimizes the total penalty.