BUSOBA 2321 MIDTERM LATEST VERIFIED SET EXAM 2025

Characteristics of a good decision - - -based on logic -considers all options and info available -sometimes gives unfavorable results 5 steps of the decision making process - -1) define problem 2) list all alternatives (options, rows) 3) identify outcomes (states of nature, columns) for each alternative 4) identify payoff for each combo of alternatives and outcome 5) pick a technique profit = - -revenue - cost revenue = - -Price x Quantity costs = - -fixed costs + (quantity x variable costs) Profit line equation - -(P-VC) x Q - FC break even point graph - -FC= intercept (P-VC)= slope x intercept = break even point indifference point - -when total costs are equal to profit indifference point equation (with price) - -(Pa-VCa)Q-FCa=(Pb-VCb)Q-FCb indifference point equation (with costs only) - -FCa+VCa*Q=FCb+VCb*Q Steps to calculating indifference point - -1) Determine Equations for each 2) Set each equation equal to each other and solve for Q 3) make indifference point table, set test points, plug back into equation 4) determine which points yield the highest profit MAXIMAX - -optimistic, choosing biggest return option (rows), then max of these options BUSOBA 2321 BUSOBA 2321 BUSOBA 2321 MAXMIN - -pessimistic, choosing the smallest return option (rows), then take the max of these options MINIMAX Regret - -1) find best outcome for each state of nature (column) 2) determine the regret for each combo - what you could have had - what you got aka best payoff - actual payoff 3) find the max regret of each option (row) 4) take the min of these max'sperfec EMV stands for - -expected monetary value EMV 's are - -the lines on your graph how to find EMV - -Value (p) + Value (p-1) EMV Max - -range of solutions ex: 0 = p = .3 A .3 = p = .7 B .7 = p = 1 C - find these by setting EMV's = to each other - this is the line that is made when all EMV's are graphed and you are looking at the maximum solutions EVwPI means - -expected value with perfect info - perfect info would tell us with certainty what outcome is going to occur EVwPI is what on a graph - -A line created by connecting the two highest points on either side of the y axis's EVwPI calculation - -Slope + y int Slope = Rise / Run (run = 1-0 bc probability from 0-1 is on the x axis) Y int = look at point on graph (left y int.) EVPI means - -expected value of perfect info (aka cost of perfect info) - it's the vertical distance between the EMV Max and the EVwPI (given a specific probability) - amount by which perfect info would increase expected payoff EVPI calculation - -EVwPI-EMV Max, where EMV Max is the equation of the line that has the highest solution at the given probability BUSOBA 2321 - simplify these lines then plug in the probability to solve for p square - decision tree - -decision, no calculation circle - decision tree - -EMV, state of nature, calculation strategic decision - -- take long time - significant consequences for incorrect decision (ex: mergers and acquisitions, buying a house) tactical decision - -- take significant amount of time - high consequences for incorrect decision (forecasting product production, buying a car) operational decision - -- take limited amount of time - low consequences for an incorrect decision (ex: assigning employees to jobs, purchasing lunch) pure strategy - -strategy not based on probability ( MAXIMIN, MINIMAX Regret) EOL means - -expected opportunity loss - best decision will be the least costly when "n" states of nature p= - -1/n EOL calculation - -SUM (regret of outcome * probability) - repeat for each option (row), choose smallest EMV calculation - -SUM (payoff of outcome * probability) - repeat for each option (row), choose largest What are the assumptions of a linear model - -1) certainty 2) proportionality 3) additivity 4) divisibility What are the properties of a linear model - -1) represents a business problem 2) max/min some quantity 3) limitations - constraints 4) must be alternatives available LHS has - -decision variables RHS has - -constraints BUSOBA 2321 BUSOBA 2321 BUSOBA 2321 Steps for linear programming - -1) define decision variables 2) make objective function (what are we max/min) 3) write out constraints 4) graph constraints (find x and y int) 5) find the optimal solution (plug in corner points to objective function) linear programming: - -continuous decision variables with the objective function and all constraints linear non linear programming - -1 constraint is non linear, decision variables are continuous integer programming - -at least one discrete decision variable with the objective function and all constraints linear non linear integer - -at least one discrete decision variable, and or at least one constraint non linear Corner Point Theorem - -optimal solution of a linear program problem occurs at one of the linear corner points of the feasible region corner points - -where constraints used to generate feasible region intersect Types of solution of to linear programming - - 1) unique optimal 2) multiple optimal 3) infeasible solution 4) unbounded unique optimal solution - -(one optimal solution) only 1 corner point will yield the optimum objective function value multiple optimal - -(more that one optimal) 2 corner points yield the same objective function value, all points on the line segment connecting the optimal corner points will also be optimal infeasible solution - -(no solution) no point that satisfies all constraints, no feasible region, no corner points unbounded - -one variable unconstrained and can go to infinity shadow price - -the change in the objective function value when the right hand side of the constraint is increased by 1 un