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Question;2-19 The feasible;region only contains points that satisfy all constraints.;2-20 A circle would;be an example of a feasible region for a linear programming problem.;2-21 The equation 5x + 7y;= 10 is linear.;2-22 The equation 3xy = 9 is linear.;2-23 The graphical;method can handle problems that involve any number of decision variables.;2-24 An objective;function represents a family of parallel lines.;2-25 When solving;linear programming problems graphically, there are an infinite number of;possible objective function lines.;2-26 For a graph;where the horizontal axis represents the variable x and the vertical axis represents the variable y, the slope of a line is the change in y when x is increased by 1.;2-27 The value of;the objective function decreases as the objective function line is moved away;from the origin.;2-28 A feasible;point on the optimal objective function line is an optimal solution.;2-29 A linear;programming problem can have multiple optimal solutions.;2-30 All constraints;in a linear programming problem are either? or? inequalities.;2-31 Linear;programming models can have either? or? inequality constraints but not both;in the same problem.;2-32 A maximization;problem can generally be characterized by having all? constraints.;2-33 If a single;optimal solution exists while using the graphical method to solve a linear;programming problem, it will exist at a corner point.;2-34 When solving a;maximization problem graphically, it is generally the goal to move the objective;function line out, away from the origin, as far as possible.;2-35 When solving a;minimization problem graphically, it is generally the goal to move the;objective function line out, away from the origin, as far as possible.


Paper#55042 | Written in 18-Jul-2015

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