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John Hoke owns Hoke s Spokes, a bicycle shop. Most of John s bicycle sales are customer orders. However, he also stocks bicycles for walk
John Hoke owns Hokes Spokes, a bicycle shop. Most of Johns bicycle sales are customer orders. However, he also stocks bicycles for walkin customers. He stocks three types of bicycles: roadracing, crosscountry and mountain. A road racing bike costs $ a crosscountry bikes cost $ and a mountain bike costs $ He sells roadracing bikes for $ crosscountry bikes for $ and mountain bikes for $ He has $ available this month to purchase bikes. Each bike must be assembled; a roadracing bike requires hours to assemble, a crosscountry bike requires hours and a mountain bike requires hours. He estimates that he and his employees have hours available to assemble bikes. He has enough space in his store to order bikes this month. Based on past sales, John wants to stock at least twice as many mountain bikes as the other two combined because mountain bikes sell better. Please show how you worked it outreasoning why in your answers: a Formulate a linear programming model for this problem. c How much would the profit per crosscountry bike have to be for the profitmaximizing solution for John to purchase any of crosscountry bikes? d Should John Hoke try to increase his budget for purchasing bikes, increase space to stock bikes or increase labor hours to assemble bikes? Why? e Suppose that Johns employees went on strike and demand an increase of $ per hour. Can he afford to pay them? f If John were to hire an additional worker for hours at $ per hour, how much additional profit would he make, if any? g If John were forced for good reason to cut down on either capital or labor hours ie changing the RHS of those constraints which one would you recommend? h If per unit profit for roadracing bike increases to $ would the optimal solution change? How about the value of the objective function? i What are the slacks on the capital, labour and storage constraints? Is there any relationship between slacks and shadow prices? Microsoft Excel Answer Report Worksheet: examplexlsBike Problem Report Created: :: PM Result: Solver found a solution. All Constraints and optimality conditions are satisfied. Solver Engine Engine: Simplex LP Solution Time: Seconds. Iterations: Subproblems: Solver Options Max Time sec Iterations Precision Max Subproblems Unlimited, Max Integer Sols Unlimited, Integer Tolerance Solve Without Integer Constraints, Assume NonNegative Objective Cell Max Original Value Cell Name Final Value $B$ Objective Function Value Variable Cells Original Value Cell Name Final Value Integer Decision Variables Value Road $B$ $C$ $D$ Decision Variables Value Crosscountry Contin Contin Decision Variables Value Mountain Contin Constraints Cell Slack $F$ $F$ $F$ $F$ Name Capital Constraint Labor Hours Constraint Storage Constraint Past Sales Cell Value Formula Status $F$$G$ Not Binding $F$$G$ Binding $F$$G$ Not Binding $F$$G$ Binding Microsoft Excel Sensitivity Report Worksheet: examplexlsBike Problem Report Created: :: PM Variable Cells Final Reduced Objective Coefficient Cell Name Value Cost $B$ $C$ $D$ Decision Variables Value Road Decision Variables Value Crosscountry Decision Variables Value Mountain Allowable Allowable Increase Decrease EE Constraints Final Shadow Constraint Allowable Allowable Value Price RH Side Increase Decrease Cell Name $F$ Capital Constraint $F$ Labor Hours Constraint $F$ Storage Constraint $F$ Past Sales EE
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