Finite Mathematics Quiz: Setting Up Linear Programming Problems
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Setting Up Linear Programming ProblemsQuestion 1 of 20

A technology startup develops mobile apps and web applications. Each mobile app requires 80 hours of development time and 20 hours of testing time. Each web application requires 60 hours of development time and 30 hours of testing time. The company has 2000 hours of development time and 600 hours of testing time available per month. Mobile apps generate $15,000 profit each, while web applications generate $12,000 profit each. The marketing team insists that the number of web applications must be at least 60% of the number of mobile apps to maintain market presence in both sectors.

What is the complete linear programming formulation for this problem? Let mm = number of mobile apps and ww = number of web applications.

Maximize P=15000m+12000wP = 15000m + 12000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0
Maximize P=15000m+12000wP = 15000m + 12000w subject to 60m+80w≤200060m + 80w \leq 2000, 30m+20w≤60030m + 20w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0
Maximize P=15000m+12000wP = 15000m + 12000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, m≥0.6wm \geq 0.6w, m≥0m \geq 0, w≥0w \geq 0
Maximize P=12000m+15000wP = 12000m + 15000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0
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Finite Mathematics Quiz

Finite Mathematics Quiz: Setting Up Linear Programming Problems

Practice Setting Up Linear Programming Problems in Finite Mathematics with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Setting Up Linear Programming Problems, giving you a quick way to practice the rules, question types, and explanations that matter most for Finite Mathematics.

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Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

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Question 1

A technology startup develops mobile apps and web applications. Each mobile app requires 80 hours of development time and 20 hours of testing time. Each web application requires 60 hours of development time and 30 hours of testing time. The company has 2000 hours of development time and 600 hours of testing time available per month. Mobile apps generate $15,000 profit each, while web applications generate $12,000 profit each. The marketing team insists that the number of web applications must be at least 60% of the number of mobile apps to maintain market presence in both sectors.

What is the complete linear programming formulation for this problem? Let mm = number of mobile apps and ww = number of web applications.

  1. Maximize P=15000m+12000wP = 15000m + 12000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0 (correct answer)
  2. Maximize P=15000m+12000wP = 15000m + 12000w subject to 60m+80w≤200060m + 80w \leq 2000, 30m+20w≤60030m + 20w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0
  3. Maximize P=15000m+12000wP = 15000m + 12000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, m≥0.6wm \geq 0.6w, m≥0m \geq 0, w≥0w \geq 0
  4. Maximize P=12000m+15000wP = 12000m + 15000w subject to 80m+60w≤200080m + 60w \leq 2000, 20m+30w≤60020m + 30w \leq 600, w≥0.6mw \geq 0.6m, m≥0m \geq 0, w≥0w \geq 0
Explanation: The correct answer is A. The objective maximizes profit: mobile apps earn $15,000 each and web applications earn $12,000 each, giving $P=15000m+12000wP = 15000m + 12000w .Developmentconstraint:80hourspermobileapp+60hoursperwebapp≤2000hours.Testingconstraint:20hourspermobileapp+30hoursperwebapp≤600hours.Marketingconstraint:webapps≥60. Development constraint: 80 hours per mobile app + 60 hours per web app ≤ 2000 hours. Testing constraint: 20 hours per mobile app + 30 hours per web app ≤ 600 hours. Marketing constraint: web apps ≥ 60% of mobile apps gives w≥0.6mw ≥ 0.6m .ChoiceBswapsthetimecoefficientsformobileandwebapps.ChoiceCreversesthemarketingconstraintto. Choice B swaps the time coefficients for mobile and web apps. Choice C reverses the marketing constraint to m≥0.6wm ≥ 0.6w $. Choice D swaps the profit coefficients in the objective function.

Question 2

A furniture manufacturer produces chairs and tables. Each chair requires 3 hours of assembly time and 2 hours of finishing time. Each table requires 4 hours of assembly time and 3 hours of finishing time. The company has 240 hours of assembly time and 180 hours of finishing time available per week. The profit is $25 per chair and $40 per table. Due to storage constraints, the company can produce at most 50 chairs per week, and market demand requires that the number of tables produced be at least half the number of chairs produced.

Which system of constraints correctly represents this linear programming problem if xx represents the number of chairs and yy represents the number of tables?

  1. 3x+4y≤2403x + 4y \leq 240, 2x+3y≤1802x + 3y \leq 180, x≤50x \leq 50, y≥0.5xy \geq 0.5x, x≥0x \geq 0, y≥0y \geq 0 (correct answer)
  2. 3x+4y≤2403x + 4y \leq 240, 2x+3y≤1802x + 3y \leq 180, x≤50x \leq 50, x≥0.5yx \geq 0.5y, x≥0x \geq 0, y≥0y \geq 0
  3. 4x+3y≤2404x + 3y \leq 240, 3x+2y≤1803x + 2y \leq 180, x≤50x \leq 50, y≥0.5xy \geq 0.5x, x≥0x \geq 0, y≥0y \geq 0
  4. 3x+4y≤2403x + 4y \leq 240, 2x+3y≤1802x + 3y \leq 180, y≤50y \leq 50, y≥0.5xy \geq 0.5x, x≥0x \geq 0, y≥0y \geq 0
Explanation: The correct answer is A. Assembly constraint: 3 hours per chair + 4 hours per table ≤ 240 hours gives 3x+4y≤2403x + 4y \leq 240. Finishing constraint: 2 hours per chair + 3 hours per table ≤ 180 hours gives 2x+3y≤1802x + 3y \leq 180. Storage constraint limits chairs to 50: x≤50x \leq 50. Market demand requires tables ≥ half the chairs: y≥0.5xy \geq 0.5x. Choice B incorrectly reverses the market constraint to x≥0.5yx \geq 0.5y. Choice C swaps the coefficients in both resource constraints. Choice D incorrectly applies the storage limit to tables instead of chairs.

Question 3

An investment firm offers two portfolio options: Conservative and Aggressive. To meet regulatory requirements, the firm must invest at least $200,000 in Conservative portfolios. Client demand requires that Aggressive portfolio investments be no more than twice the Conservative portfolio investments. The firm has $800,000 available for investment. Conservative portfolios yield 4% annual return while Aggressive portfolios yield 7% annual return, but the firm's risk management policy limits total Aggressive investments to $400,000.

If CC represents thousands of dollars invested in Conservative portfolios and AA represents thousands of dollars invested in Aggressive portfolios, which constraint is incorrectly formulated?

  1. C+A≤800C + A \leq 800 (budget constraint using thousands of dollars)
  2. C≥200C \geq 200 (minimum Conservative investment requirement) (correct answer)
  3. A≤2CA \leq 2C (Aggressive investment limitation relative to Conservative)
  4. A≤400A \leq 400 (maximum Aggressive investment limit)
Explanation: The correct answer is B. Since CC represents thousands of dollars, the minimum $200,000 investment in Conservative portfolios should be written as $C≥200C \geq 200 ,notthevalueshowninchoiceBwhichwouldrepresent, not the value shown in choice B which would represent 200 thousand thousand = 200million.Allotherconstraintsarecorrectlyformulated:thebudgetconstraint200 million. All other constraints are correctly formulated: the budget constraint C+A≤800C + A \leq 800 properlyusesthousands,properly uses thousands, A≤2CA \leq 2C correctlycapturesthatAggressiveinvestmentscan′texceedtwiceConservativeinvestments,andcorrectly captures that Aggressive investments can't exceed twice Conservative investments, and A≤400A \leq 400 $ correctly represents the $400,000 limit in thousands.

Question 4

A manufacturing plant produces electric motors and generators. Each motor requires 4 hours on Machine A and 6 hours on Machine B. Each generator requires 8 hours on Machine A and 3 hours on Machine B. Machine A is available for 320 hours per week and Machine B is available for 240 hours per week. The plant must produce at least 15 motors weekly to fulfill standing orders. Additionally, environmental regulations limit the combined weekly production to at most 50 units total. Motors sell for $800 each and generators sell for $1200 each. In the linear programming setup, what does the constraint $m+g≤50m + g \leq 50 $ represent?

  1. The total machine hours used cannot exceed 50 hours per week
  2. The environmental regulation limiting combined production to 50 units maximum (correct answer)
  3. The minimum production requirement for motors and generators combined
  4. The budget constraint limiting total production costs to $50,000
Explanation: The correct answer is B. The constraint m+g≤50m + g \leq 50 represents the environmental regulation that limits the total combined production of motors and generators to at most 50 units per week. Choice A is incorrect because machine hours would involve the time coefficients (4, 6, 8, 3), not just m+gm + g. Choice C is wrong because the constraint uses ≤, indicating a maximum limit, not a minimum requirement (which would use ≥). Choice D is incorrect because costs would involve the selling prices ($800, $1200) as coefficients, not the simple sum $m+gm + g $.

Question 5

An electronics retailer stocks two models of tablets: BasicTab and ProTab. Each BasicTab requires 2 cubic feet of storage space and ties up $200 in inventory investment. Each ProTab requires 3 cubic feet of storage space and ties up $450 in inventory investment. The store has 600 cubic feet of storage space and can invest up to $40,000 in tablet inventory. BasicTab generates $50 profit per unit while ProTab generates $120 profit per unit. Store policy requires maintaining at least 30 BasicTab units in stock, and supplier agreements limit ProTab orders to at most 75 units.

In formulating this as a linear programming problem with bb = BasicTab units and tt = ProTab units, which statement about the constraints is false?

  1. The storage constraint can be written as 2b+3t≤6002b + 3t \leq 600
  2. The inventory investment constraint is 200b+450t≤40000200b + 450t \leq 40000
  3. The minimum BasicTab requirement constraint is b≥30b \geq 30
  4. The supplier limitation constraint should be written as t≥75t \geq 75 (correct answer)
Explanation: The correct answer is D. The supplier agreement limits ProTab orders to at most 75 units, so the constraint should be t≤75t \leq 75, not t≥75t \geq 75. Choice D incorrectly states ≥ 75, which would require at least 75 ProTab units rather than limiting to at most 75 units. Choice A correctly represents storage: 2 cubic feet per BasicTab + 3 cubic feet per ProTab ≤ 600 total cubic feet. Choice B correctly represents the investment limit: $200 per BasicTab + $450 per ProTab ≤ $40,000. Choice C correctly represents the minimum BasicTab requirement of at least 30 units.

Question 6

A pharmaceutical company produces two types of vitamin supplements: MultiVit and CalciumPlus. The production process requires three resources: ingredient A, ingredient B, and packaging material. Each bottle of MultiVit uses 2 units of ingredient A, 1 unit of ingredient B, and 1 unit of packaging. Each bottle of CalciumPlus uses 1 unit of ingredient A, 3 units of ingredient B, and 2 units of packaging. The company has 120 units of ingredient A, 150 units of ingredient B, and 100 units of packaging available daily. If the company must produce at least 20 bottles of MultiVit and the total production cannot exceed 80 bottles per day, what is the correct objective function to maximize profit given that MultiVit generates $8 profit per bottle and CalciumPlus generates $6 profit per bottle?

  1. Maximize P=8x+6yP = 8x + 6y where xx = bottles of MultiVit, yy = bottles of CalciumPlus (correct answer)
  2. Maximize P=6x+8yP = 6x + 8y where xx = bottles of MultiVit, yy = bottles of CalciumPlus
  3. Minimize P=8x+6yP = 8x + 6y where xx = bottles of MultiVit, yy = bottles of CalciumPlus
  4. Maximize P=8x+6yP = 8x + 6y where xx = bottles of CalciumPlus, yy = bottles of MultiVit
Explanation: The correct answer is A. The objective is to maximize profit, so we need 'Maximize'. MultiVit generates $8 per bottle and CalciumPlus generates $6 per bottle. With $xx =bottlesofMultiVitand= bottles of MultiVit and yy =bottlesofCalciumPlus,theobjectivefunctionis= bottles of CalciumPlus, the objective function is P=8x+6yP = 8x + 6y .ChoiceBswapstheprofitcoefficients.ChoiceCuses′Minimize′insteadof′Maximize′.ChoiceDincorrectlydefinesthevariableswith. Choice B swaps the profit coefficients. Choice C uses 'Minimize' instead of 'Maximize'. Choice D incorrectly defines the variables with xx asCalciumPlusandas CalciumPlus and yy $ as MultiVit.

Question 7

A chemical company blends two fertilizer compounds: NitroBlend and PhosphoMax. Each ton of NitroBlend contains 40% nitrogen, 20% phosphorus, and 15% potassium. Each ton of PhosphoMax contains 25% nitrogen, 35% phosphorus, and 30% potassium. A customer order requires a blend with at least 12 tons of nitrogen, at least 9 tons of phosphorus, and at least 6 tons of potassium. The company wants to minimize the total weight of the blend to reduce shipping costs.

Let nn = tons of NitroBlend and pp = tons of PhosphoMax. Which constraint correctly represents the potassium requirement?

  1. 15n+30p≥615n + 30p \geq 6
  2. 0.30n+0.15p≥60.30n + 0.15p \geq 6
  3. 0.15n+0.30p≥60.15n + 0.30p \geq 6 (correct answer)
  4. 0.15n+0.30p≤60.15n + 0.30p \leq 6
Explanation: When you encounter linear programming problems involving mixtures or blends, you need to translate percentage compositions into constraint inequalities. The key is correctly converting percentages to decimals and setting up the "at least" requirement. For the potassium constraint, you need to calculate the total potassium contributed by both compounds. NitroBlend contains 15% potassium, which converts to 0.15 as a decimal. So nn tons of NitroBlend contributes 0.15n0.15n tons of potassium. PhosphoMax contains 30% potassium (0.30 as a decimal), so pp tons contributes 0.30p0.30p tons of potassium. Since the order requires "at least 6 tons" of potassium, the total must be greater than or equal to 6: 0.15n+0.30p≥60.15n + 0.30p \geq 6. Choice A (15n+30p≥615n + 30p \geq 6) incorrectly uses the percentages as whole numbers instead of converting them to decimals. This would represent a constraint where you need only 6 units when the percentages are treated as 1500% and 3000% respectively. Choice B (0.30n+0.15p≥60.30n + 0.15p \geq 6) swaps the coefficients, incorrectly assigning NitroBlend's potassium percentage to PhosphoMax and vice versa. Choice D (0.15n+0.30p≤60.15n + 0.30p \leq 6) has the correct coefficients but uses "less than or equal to" instead of "greater than or equal to," which would limit potassium to a maximum of 6 tons rather than requiring at least 6 tons. Always convert percentages to decimals in constraint equations, and ensure your inequality direction matches the requirement ("at least" means ≥, "at most" means ≤).

Question 8

A bakery produces artisan bread and pastries. Each loaf of bread requires 0.5 kg of flour and 0.2 hours of baking time. Each batch of pastries requires 0.3 kg of flour and 0.4 hours of baking time. The bakery has 60 kg of flour and 30 hours of baking time available daily. Due to oven capacity, bread production is limited to 80 loaves per day. The bakery's contract with a local café requires delivering at least 40 batches of pastries daily. If bb represents loaves of bread and pp represents batches of pastries, which constraint represents the flour limitation?

  1. 0.5b+0.3p≤600.5b + 0.3p \leq 60 (correct answer)
  2. 0.3b+0.5p≤600.3b + 0.5p \leq 60
  3. 0.2b+0.4p≤600.2b + 0.4p \leq 60
  4. 0.5b+0.3p≥600.5b + 0.3p \geq 60
Explanation: The correct answer is A. Each loaf of bread uses 0.5 kg of flour and each batch of pastries uses 0.3 kg of flour. The total flour consumption must not exceed 60 kg available, giving 0.5b+0.3p≤600.5b + 0.3p \leq 60. Choice B swaps the flour coefficients for bread and pastries. Choice C uses the baking time coefficients (0.2 and 0.4) instead of flour coefficients. Choice D uses the wrong inequality direction, suggesting the bakery must use at least 60 kg of flour rather than at most.

Question 9

A craft furniture workshop produces two models of chairs: a Rocker and a Glider. The profit is $60 for each Rocker and $75 for each Glider. Production requires two stages: fabrication and finishing. For fabrication, each Rocker requires 2 hours and each Glider requires 4 hours. The workshop has 120 hours of fabrication time available per week. For finishing, each Rocker requires 3 hours and each Glider requires 2 hours. The workshop has 100 hours of finishing time available per week. Due to a marketing agreement, the number of Gliders produced must be at least one-third of the number of Rockers produced.

Let rr be the number of Rockers and gg be the number of Gliders produced per week. Which of the following systems correctly formulates the constraints for this linear programming problem?

  1. {2r+4g≤1203r+2g≤100g≤13rr≥0,g≥0\begin{cases} 2r + 4g \le 120 \\ 3r + 2g \le 100 \\ g \le \frac{1}{3}r \\ r \ge 0, g \ge 0 \end{cases}
  2. {2r+3g≤1204r+2g≤100g≥13rr≥0,g≥0\begin{cases} 2r + 3g \le 120 \\ 4r + 2g \le 100 \\ g \ge \frac{1}{3}r \\ r \ge 0, g \ge 0 \end{cases}
  3. {2r+4g≤1203r+2g≤100g≥3rr≥0,g≥0\begin{cases} 2r + 4g \le 120 \\ 3r + 2g \le 100 \\ g \ge 3r \\ r \ge 0, g \ge 0 \end{cases}
  4. {2r+4g≤1203r+2g≤100g≥13rr≥0,g≥0\begin{cases} 2r + 4g \le 120 \\ 3r + 2g \le 100 \\ g \ge \frac{1}{3}r \\ r \ge 0, g \ge 0 \end{cases} (correct answer)
Explanation: Let rr be the number of Rockers and gg be the number of Gliders. The fabrication constraint is based on the 120 available hours: 2r+4g≤1202r + 4g \le 120. The finishing constraint is based on the 100 available hours: 3r+2g≤1003r + 2g \le 100. The marketing agreement states that the number of Gliders (gg) must be at least (≥\ge) one-third of the number of Rockers (rr), which translates to g≥13rg \ge \frac{1}{3}r. Finally, the non-negativity constraints are r≥0r \ge 0 and g≥0g \ge 0. This set of constraints matches option D. Distractor A incorrectly uses ≤\le for the marketing constraint. Distractor B mixes up the coefficients for rr and gg in the fabrication and finishing constraints. Distractor C incorrectly formulates the marketing constraint as g≥3rg \ge 3r, which would mean the number of gliders must be at least three times the number of rockers.

Question 10

An investment manager is allocating $500,000 for a client into two funds: a stock fund and a bond fund. The stock fund has an expected return of 10% and the bond fund has an expected return of 4%. The client has several requirements: at least $100,000 must be invested in the bond fund, and the amount invested in the stock fund must not be more than twice the amount invested in the bond fund.

Let ss be the amount invested in the stock fund and bb be the amount invested in the bond fund. The manager's goal is to maximize the expected return. Which of the following is the complete set of constraints for this allocation problem?

  1. {s+b≤500000b≥100000s≤2bs≥0,b≥0\begin{cases} s + b \le 500000 \\ b \ge 100000 \\ s \le 2b \\ s \ge 0, b \ge 0 \end{cases} (correct answer)
  2. {s+b=500000b≥100000s≤2bs≥0,b≥0\begin{cases} s + b = 500000 \\ b \ge 100000 \\ s \le 2b \\ s \ge 0, b \ge 0 \end{cases}
  3. {s+b≤500000b≥100000b≤2ss≥0,b≥0\begin{cases} s + b \le 500000 \\ b \ge 100000 \\ b \le 2s \\ s \ge 0, b \ge 0 \end{cases}
  4. {s+b≤500000b≤100000s≥2bs≥0,b≥0\begin{cases} s + b \le 500000 \\ b \le 100000 \\ s \ge 2b \\ s \ge 0, b \ge 0 \end{cases}
Explanation: The total amount allocated cannot exceed $500,000, so $s + b \le 500000.′Atleast$100,000mustbeinvestedinthebondfund′translatesto$b≥100000. 'At least $100,000 must be invested in the bond fund' translates to $b \ge 100000. 'The amount invested in the stock fund (ss) must not be more than (≤\le) twice the amount invested in the bond fund ($2b$)' translates to s≤2bs \le 2b. Non-negativity constraints are s≥0s \ge 0 and b≥0b \ge 0. This matches system A. Distractor B incorrectly assumes the entire 500,000mustbeinvested(500,000 must be invested (s+b=500000),whichisnotstated.DistractorCincorrectlyreversesthevariablesintherisk−toleranceconstraint,stating), which is not stated. Distractor C incorrectly reverses the variables in the risk-tolerance constraint, stating b \le 2s$. Distractor D reverses the inequalities for both the bond investment minimum and the risk-tolerance constraint.

Question 11

A factory manager is scheduling production for two models of a device, Model A and Model B. The factory operates for at most 8 hours (480 minutes) per day. Model A takes 15 minutes to produce and yields a profit of $30. Model B takes 12 minutes to produce and yields a profit of $28. The factory has a daily supply of 200 specialized components, of which Model A requires one and Model B requires one. To meet demand, the company must produce at least 10 units of Model A and at least 15 units of Model B each day.

Let xx be the number of units of Model A and yy be the number of units of Model B. The objective is to maximize profit. Which is the correct system of constraints?

  1. {15x+12y≤480x+y≤200x≥10y≥15\begin{cases} 15x + 12y \le 480 \\ x+y \le 200 \\ x \ge 10 \\ y \ge 15 \end{cases} (correct answer)
  2. {x+y≤48015x+12y≤200x≥10y≥15\begin{cases} x + y \le 480 \\ 15x+12y \le 200 \\ x \ge 10 \\ y \ge 15 \end{cases}
  3. {30x+28y≤480x+y≤200x≥10y≥15\begin{cases} 30x + 28y \le 480 \\ x+y \le 200 \\ x \ge 10 \\ y \ge 15 \end{cases}
  4. {15x+12y≤8x+y≤200x≤10y≤15\begin{cases} 15x + 12y \le 8 \\ x+y \le 200 \\ x \le 10 \\ y \le 15 \end{cases}
Explanation: The total production time cannot exceed 480 minutes: 15x+12y≤48015x + 12y \le 480. The total number of components used cannot exceed 200: x+y≤200x + y \le 200. The minimum demand for Model A is 10 units: x≥10x \ge 10. The minimum demand for Model B is 15 units: y≥15y \ge 15. The system in A correctly represents all these constraints. Distractor B swaps the coefficients and bounds for the time and component constraints. Distractor C incorrectly uses profit values as coefficients in the time constraint. Distractor D uses hours instead of minutes for the time constraint and reverses the inequalities for the demand constraints.

Question 12

A small firm manufactures two types of electronic kits, Standard and Deluxe. To fill a special order, the firm must produce a total of at least 100 kits. For this order, the number of Deluxe kits produced cannot exceed the number of Standard kits by more than 20. The firm also knows that the number of Standard kits must be no more than 80. The cost to produce a Standard kit is $50 and a Deluxe kit is $75. The firm wants to minimize its production costs for this order.

Let ss be the number of Standard kits and dd be the number of Deluxe kits. Which of the following is a complete and correct set of constraints for this problem?

  1. {s+d≥100d≤s+20s≤80s≥0,d≥0\begin{cases} s + d \ge 100 \\ d \le s + 20 \\ s \le 80 \\ s \ge 0, d \ge 0 \end{cases} (correct answer)
  2. {s+d≤100d≤s−20s≤80s≥0,d≥0\begin{cases} s + d \le 100 \\ d \le s - 20 \\ s \le 80 \\ s \ge 0, d \ge 0 \end{cases}
  3. {s+d≥100s≤d+20s≤80s≥0,d≥0\begin{cases} s + d \ge 100 \\ s \le d + 20 \\ s \le 80 \\ s \ge 0, d \ge 0 \end{cases}
  4. {s+d≥100d≥s+20s≤80s≥0,d≥0\begin{cases} s + d \ge 100 \\ d \ge s + 20 \\ s \le 80 \\ s \ge 0, d \ge 0 \end{cases}
Explanation: The total number of kits must be at least 100: s+d≥100s + d \ge 100. The number of Deluxe kits (dd) cannot exceed the number of Standard kits (ss) by more than 20. This can be written as d−s≤20d - s \le 20, which rearranges to d≤s+20d \le s + 20. The number of Standard kits must be no more than 80: s≤80s \le 80. Finally, non-negativity constraints are s≥0,d≥0s \ge 0, d \ge 0. This matches system A. Distractor B uses the wrong inequality for the total production and incorrectly formulates the relationship between ss and dd. Distractor C misinterprets 'Deluxe kits cannot exceed Standard kits by more than 20' as s≤d+20s \le d+20. Distractor D reverses the inequality for the relationship between ss and dd.

Question 13

A farmer has 200 acres of land available for planting two crops: wheat and barley. The profit per acre is $150 for wheat and $120 for barley. The farmer has a total of 450 hours of labor available. Wheat requires 3 hours of labor per acre, while barley requires 2 hours of labor per acre. To manage soil health, the farmer decides that the acreage devoted to barley must be at least 25% of the acreage devoted to wheat.

Let ww be the acres of wheat and bb be the acres of barley. Which of the following systems correctly represents the constraints for maximizing profit?

  1. {w+b≤2003w+2b≤450w≥0.25bw≥0,b≥0\begin{cases} w + b \le 200 \\ 3w + 2b \le 450 \\ w \ge 0.25b \\ w \ge 0, b \ge 0 \end{cases}
  2. {w+b≤2003w+2b≤450b≥0.25ww≥0,b≥0\begin{cases} w + b \le 200 \\ 3w + 2b \le 450 \\ b \ge 0.25w \\ w \ge 0, b \ge 0 \end{cases} (correct answer)
  3. {w+b≤2003w+2b≤450b≤0.25ww≥0,b≥0\begin{cases} w + b \le 200 \\ 3w + 2b \le 450 \\ b \le 0.25w \\ w \ge 0, b \ge 0 \end{cases}
  4. {150w+120b≤2003w+2b≤450b≥0.25ww≥0,b≥0\begin{cases} 150w + 120b \le 200 \\ 3w + 2b \le 450 \\ b \ge 0.25w \\ w \ge 0, b \ge 0 \end{cases}
Explanation: When you encounter a linear programming problem like this, you need to translate each real-world constraint into mathematical inequalities. The key is carefully reading what each constraint actually says. Let's work through each constraint systematically. First, the farmer has 200 acres total, so w+b≤200w + b \le 200. Second, with 450 hours of labor available and wheat requiring 3 hours per acre while barley requires 2 hours per acre, we get 3w+2b≤4503w + 2b \le 450. Third, since both crops require non-negative acreage, we need w≥0,b≥0w \ge 0, b \ge 0. The critical constraint is the soil health requirement: "the acreage devoted to barley must be at least 25% of the acreage devoted to wheat." This translates to b≥0.25wb \ge 0.25w, meaning barley acreage should be greater than or equal to one-quarter of wheat acreage. Choice B correctly captures all these constraints. Choice A reverses the soil health inequality to w≥0.25bw \ge 0.25b, which would mean wheat must be at least 25% of barley—the opposite of what's stated. Choice C uses b≤0.25wb \le 0.25w, making barley at most 25% of wheat, again contradicting the requirement. Choice D incorrectly uses the profit coefficients (150 and 120) in the land constraint instead of recognizing that land is measured in acres, not dollars. Study tip: In constraint problems, always double-check your inequality directions by plugging in simple numbers. If barley must be "at least 25%" of wheat, then when wheat = 100, barley should be able to equal 25 or more, confirming b≥0.25wb \ge 0.25w.

Question 14

A company has a marketing budget of $12,000 to spend on social media posts and radio advertisements. Each social media post costs $50 and is expected to reach 2,000 people. Each radio ad costs $300 and is expected to reach 9,000 people. The marketing team has decided they need at least 10 radio ads. Also, the number of social media posts must be at least four times the number of radio ads to create a synergistic effect.

Let ss be the number of social media posts and rr be the number of radio ads. The goal is to maximize the total reach. Which of the following is the correct formulation of the problem's constraints?

  1. {2000s+9000r≤12000r≥10s≥4rs≥0,r≥0\begin{cases} 2000s + 9000r \le 12000 \\ r \ge 10 \\ s \ge 4r \\ s \ge 0, r \ge 0 \end{cases}
  2. {50s+300r≤12000r≥10s≥4rs≥0,r≥0\begin{cases} 50s + 300r \le 12000 \\ r \ge 10 \\ s \ge 4r \\ s \ge 0, r \ge 0 \end{cases} (correct answer)
  3. {50s+300r≤12000r≥10r≥4ss≥0,r≥0\begin{cases} 50s + 300r \le 12000 \\ r \ge 10 \\ r \ge 4s \\ s \ge 0, r \ge 0 \end{cases}
  4. {s+r≤12000r≥10s≤4rs≥0,r≥0\begin{cases} s + r \le 12000 \\ r \ge 10 \\ s \le 4r \\ s \ge 0, r \ge 0 \end{cases}
Explanation: This is a linear programming problem where you need to translate real-world constraints into mathematical inequalities. When setting up these problems, carefully match each constraint in the problem statement to its correct mathematical expression. The budget constraint uses costs, not reach numbers. Social media posts cost $50 each and radio ads cost $300 each, so the total cost is $50s+300r50s + 300r ,whichcannotexceedthe$12,000budget:$, which cannot exceed the $12,000 budget: $50s + 300r \le 12000.Theproblemstates"atleast10radioads,"givingus. The problem states "at least 10 radio ads," giving us r \ge 10.Forthesynergisticeffect,"socialmediapostsmustbeatleastfourtimesthenumberofradioads"means. For the synergistic effect, "social media posts must be at least four times the number of radio ads" means s \ge 4r.Finally,youcannothavenegativeadvertisements,so. Finally, you cannot have negative advertisements, so s \ge 0, r \ge 0$$. Answer choice A incorrectly uses the reach values (2,000 and 9,000) in the budget constraint instead of the costs ($50 and $300). This is a common error when students confuse the objective function (what you're maximizing - total reach) with the constraint coefficients (costs). Answer choice C has the synergy constraint backwards, stating $$r \ge 4sinsteadofinstead ofs \ge 4r$$. This would require radio ads to be at least four times the social media posts, opposite of what's stated. Answer choice D makes multiple errors: it uses s+r≤12000s + r \le 12000 (ignoring actual costs) and incorrectly writes the synergy constraint as s≤4rs \le 4r. Study tip: In linear programming problems, always identify what each variable represents, then carefully translate each sentence into math. Double-check that you're using costs for budget constraints, not the values you're trying to maximize.

Question 15

A coffee company is creating a new blend from two types of coffee beans: Arabica and Robusta. The company has 500 pounds of Arabica and 400 pounds of Robusta in stock. The new blend will be sold in 1-pound bags. The cost of Arabica beans is $12 per pound and Robusta is $8 per pound. The blend must contain at least 30% Arabica beans by weight. To ensure a bold flavor, the weight of Robusta beans must be no more than the weight of Arabica beans.

Let aa be the pounds of Arabica beans and rr be the pounds of Robusta beans used to create the blend. The company's goal is to minimize the cost of the beans used. Which of the following inequalities is NOT a valid constraint for this problem?

  1. a≤500a \le 500
  2. r≤ar \le a
  3. a≥0.30(a+r)a \ge 0.30(a+r)
  4. a+r≥1a+r \ge 1 (correct answer)
Explanation: Let's analyze the constraints. The company has 500 pounds of Arabica available, so a≤500a \le 500. It has 400 pounds of Robusta, so r≤400r \le 400. 'The weight of Robusta beans (rr) must be no more than (≤\le) the weight of Arabica beans (aa)', which is r≤ar \le a. 'The blend must contain at least 30% Arabica beans by weight' means the amount of Arabica (aa) must be at least 30% of the total weight (a+ra+r), so a≥0.30(a+r)a \ge 0.30(a+r). The constraints in A, B, and C are all valid. The constraint a+r≥1a+r \ge 1 suggests that the total blend must be at least 1 pound. While true in a practical sense to make even one bag, it is not a constraint given in the problem description; the problem is about the composition and availability of beans for a blend of any size. The core task is to determine the optimal ratio and total amount based on resource limits, not to meet a minimum production quota. Thus, this is not a specified constraint. Distractor A is a valid constraint on Arabica availability. Distractor B correctly models the flavor requirement. Distractor C correctly models the minimum percentage of Arabica.

Question 16

A pet food company is creating a new high-protein dog food by mixing two ingredients: a meat-based product and a grain-based product. Each kilogram of the meat product costs $2.50 and contains 0.5 kg of protein and 0.1 kg of fat. Each kilogram of the grain product costs $1.00 and contains 0.1 kg of protein and 0.05 kg of fat. To meet nutritional standards, each bag of the final mix must weigh exactly 10 kilograms and contain at least 2 kg of protein. Additionally, the fat content must be between 0.6 kg and 0.8 kg, inclusive.

Let mm be the kilograms of the meat product and gg be the kilograms of the grain product per bag. The company wants to minimize production cost. Which of the following constraints correctly represents the requirement for fat content in one bag of the mix?

  1. 0.6≤0.1m+0.05g≤0.80.6 \le 0.1m + 0.05g \le 0.8 (correct answer)
  2. 0.1m+0.05g≥0.60.1m + 0.05g \ge 0.6
  3. 0.1m+0.05g≤0.80.1m + 0.05g \le 0.8
  4. 6≤m+0.5g≤86 \le m + 0.5g \le 8
Explanation: The total amount of fat in the mix is the sum of the fat from each ingredient: 0.10.1 kg of fat for every kg of meat product (mm) and 0.050.05 kg of fat for every kg of grain product (gg). So, the total fat is 0.1m+0.05g0.1m + 0.05g. The problem states the fat content must be 'between 0.6 kg and 0.8 kg, inclusive'. This means the total fat must be greater than or equal to 0.6 AND less than or equal to 0.8. This is correctly written as the double inequality 0.6≤0.1m+0.05g≤0.80.6 \le 0.1m + 0.05g \le 0.8. Distractor B only includes the minimum requirement for fat. Distractor C only includes the maximum requirement for fat. Distractor D incorrectly uses coefficients and combines variables in a way that does not represent the fat content.

Question 17

A bakery produces two types of cakes, chocolate and vanilla. The bakery's goal is to maximize its daily profit. Each chocolate cake sells for $25 and has ingredients and labor costs totaling $10. Each vanilla cake sells for $20 and costs $8 to produce. The baking process for each cake requires oven space and time. A chocolate cake requires 2 units of oven space-hours, and a vanilla cake requires 1 unit. The total available oven space-hours per day is 80. The bakery can package at most 50 cakes in total per day.

Let cc be the number of chocolate cakes and vv be the number of vanilla cakes. Which of the following is the correct objective function PP to be maximized?

  1. P=25c+20vP = 25c + 20v
  2. P=10c+8vP = 10c + 8v
  3. P=15c+12vP = 15c + 12v (correct answer)
  4. P=35c+28vP = 35c + 28v
Explanation: The objective is to maximize profit. Profit is calculated as (Selling Price - Costs). For a chocolate cake, the profit is $25 - $10 = $15. For a vanilla cake, the profit is $20 - $8 = $12. Therefore, the total profit function $Ptobemaximizedisto be maximized isP = 15c + 12v$. Distractor A represents the total revenue, not the profit. Distractor B represents the total cost, which should be minimized, not maximized. Distractor D incorrectly calculates profit by adding costs to the selling price instead of subtracting them.

Question 18

A recycling center processes two types of materials, Type A and Type B. The center earns a profit of $5 per ton of Type A and $8 per ton of Type B. The center can process a maximum of 100 tons of material per day in total. Processing requires a sorting machine, which can run for at most 8 hours (480 minutes) per day. It takes 3 minutes to sort a ton of Type A and 6 minutes to sort a ton of Type B. Furthermore, due to local regulations, the amount of Type B material processed cannot be less than half the amount of Type A material processed.

Let xx be the tons of Type A material and yy be the tons of Type B material. The center's goal is to maximize daily profit. Which of the following is the complete set of constraints for this problem?

  1. {x+y≤1003x+6y≤480y≥2xx≥0,y≥0\begin{cases} x + y \le 100 \\ 3x + 6y \le 480 \\ y \ge 2x \\ x \ge 0, y \ge 0 \end{cases}
  2. {x+y≤1003x+6y≤480y≥0.5xx≥0,y≥0\begin{cases} x + y \le 100 \\ 3x + 6y \le 480 \\ y \ge 0.5x \\ x \ge 0, y \ge 0 \end{cases} (correct answer)
  3. {5x+8y≤1003x+6y≤480x≥0.5yx≥0,y≥0\begin{cases} 5x + 8y \le 100 \\ 3x + 6y \le 480 \\ x \ge 0.5y \\ x \ge 0, y \ge 0 \end{cases}
  4. {x+y≤1003x+6y≤8y≤0.5xx≥0,y≥0\begin{cases} x + y \le 100 \\ 3x + 6y \le 8 \\ y \le 0.5x \\ x \ge 0, y \ge 0 \end{cases}
Explanation: The total tonnage processed cannot exceed 100: x+y≤100x + y \le 100. The total sorting time cannot exceed 480 minutes: 3x+6y≤4803x + 6y \le 480. The local regulation states that Type B (yy) cannot be less than (is greater than or equal to) half of Type A (0.5x0.5x), so y≥0.5xy \ge 0.5x. Non-negativity constraints are x≥0,y≥0x \ge 0, y \ge 0. This system matches option B. Distractor A incorrectly represents the regulation as y≥2xy \ge 2x. Distractor C incorrectly uses profit coefficients in the tonnage constraint and reverses the variables in the regulation constraint. Distractor D uses hours instead of minutes for the time constraint and reverses the inequality in the regulation constraint.

Question 19

A pharmaceutical company is producing a nutritional supplement using two active ingredients, Ingredient X and Ingredient Y. The goal is to determine the optimal quantity of each ingredient to include in one dose to minimize its cost. A single dose must contain at least 12 mg of Vitamin A, at least 15 mg of Vitamin B, and no more than 8 mg of Vitamin C. Ingredient X costs $0.05 per gram and contains 2 mg of Vitamin A, 5 mg of Vitamin B, and 2 mg of Vitamin C per gram. Ingredient Y costs $0.08 per gram and contains 4 mg of Vitamin A, 1 mg of Vitamin B, and 1 mg of Vitamin C per gram.

Let xx be the number of grams of Ingredient X and yy be the number of grams of Ingredient Y in one dose. Which is the correct objective function CC to minimize, subject to the problem's constraints?

  1. C=2x+4yC = 2x + 4y
  2. C=12(2x+4y)+15(5x+y)+8(2x+y)C = 12(2x+4y) + 15(5x+y) + 8(2x+y)
  3. C=0.05x+0.08yC = 0.05x + 0.08y (correct answer)
  4. C=x+yC = x + y
Explanation: The problem asks to set up a linear programming problem to minimize the cost of one dose. The variables are defined as xx (grams of Ingredient X) and yy (grams of Ingredient Y). The cost of Ingredient X is $0.05 per gram, and the cost of Ingredient Y is $0.08 per gram. Therefore, the total cost $Cofonedoseisthesumofthecostsoftheingredientsused:of one dose is the sum of the costs of the ingredients used:C = 0.05x + 0.08y$. The objective is to minimize this function. Distractor A creates a function based on the Vitamin A content, which is a constraint, not the objective. Distractor B nonsensically combines the vitamin requirements with the vitamin contents into an objective function. Distractor D creates an objective function to minimize the total weight of the ingredients, not the cost.

Question 20

A logistics company operates two types of delivery trucks: small trucks and large trucks. Small trucks can carry up to 3 tons and cost $200 per day to operate. Large trucks can carry up to 8 tons and cost $350 per day to operate. The company needs to deliver at least 50 tons of cargo daily and has a budget of $3000 per day for truck operations. Union agreements require that the number of small trucks used cannot be more than three times the number of large trucks used. If the goal is to minimize the total operating cost while meeting all constraints, which of the following represents the correct constraint for the cargo capacity requirement?

  1. 200s+350l≥50200s + 350l \geq 50 where ss = small trucks, ll = large trucks
  2. 3s+8l≤503s + 8l \leq 50 where ss = small trucks, ll = large trucks
  3. 8s+3l≥508s + 3l \geq 50 where ss = small trucks, ll = large trucks
  4. 3s+8l≥503s + 8l \geq 50 where ss = small trucks, ll = large trucks (correct answer)
Explanation: When you encounter a linear programming problem like this, you need to translate real-world constraints into mathematical inequalities. The key is carefully matching the given information to the correct mathematical expression. Let's identify what we know: small trucks carry 3 tons each, large trucks carry 8 tons each, and the company needs at least 50 tons delivered daily. Since we need "at least" 50 tons, we're looking for a "greater than or equal to" constraint (≥). The correct answer is D: 3s+8l≥503s + 8l \geq 50. This properly represents that 3 tons per small truck times the number of small trucks, plus 8 tons per large truck times the number of large trucks, must equal or exceed 50 tons total. Choice A (200s+350l≥50200s + 350l \geq 50) confuses capacity with cost. The values 200 and 350 represent daily operating costs, not cargo capacity, so this constraint would be meaningless for cargo requirements. Choice B (3s+8l≤503s + 8l \leq 50) has the wrong inequality direction. Using "less than or equal to" would mean the company wants to deliver at most 50 tons, which contradicts the requirement of delivering at least 50 tons. Choice C (8s+3l≥508s + 3l \geq 50) switches the capacity coefficients. This incorrectly assigns 8 tons capacity to small trucks and 3 tons to large trucks, which is backwards from the given information. Study tip: In linear programming problems, always double-check that your coefficients match the correct variables and that your inequality directions align with words like "at least" (≥) versus "at most" (≤).