This problem is based on the classic order-up-to-level (M.L) inventory policy with a reorder point (L),...
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This problem is based on the classic order-up-to-level (M.L) inventory policy with a reorder point (L), a maximum inventory level (M), random demand, and random lead time. A company is selling a non-perishable item. Consider an (M,L) inventory system, in which the procurement quantity Q is defined by Q = {M (M-I if I<L if IZL I is the inventory on hand plus on order at the end of a month M is the maximum inventory level L is the reorder point Use simulation to investigate an (M,L) inventory system with the following properties: The inventory position is reviewed at the end of each month (fixed review) 1 2 3 4 Backordering is allowed at a cost of $4 per item short each month When an order arrives, it will first be used to relieve the backorder. Lead time is uniformly distributed on the interval [0.25, 1.25]. Beginning inventory is 50 units and there are no orders outstanding. Holding costs are $1 per unit in inventory per month. When an order is placed, its cost is $60 + $5Q where $60 is the ordering cost and $5 is the cost of the item. The time between demands is exponentially distributed with a mean of 1/15 month. The size of demands follows this distribution: Demand Probability 0.5 0.25 0.125 0.125 (a) Create a simulation model to evaluate the above inventory problem. (b) Make ten independent replications, each of run length 100 months preceded by a 12 month initialization period, for the (M, L) = (50, 30) policy. (Hint: Run each individual simulation trial using the "One Trial" worksheet in the Example2.8RefrigInventory spreadsheet.) Record each of the ten independent replication results for average ending inventory, average units ordered per month, and average monthly costs. Adjust worksheet graph as needed to reflect average monthly inventory frequencies. (c) Estimate long-run mean monthly cost with a 95% confidence interval. (d) Using the results of part (a) and (b), estimate the total number of replications needed to estimate mean monthly cost within $4. This problem is based on the classic order-up-to-level (M.L) inventory policy with a reorder point (L), a maximum inventory level (M), random demand, and random lead time. A company is selling a non-perishable item. Consider an (M,L) inventory system, in which the procurement quantity Q is defined by Q = {M (M-I if I<L if IZL I is the inventory on hand plus on order at the end of a month M is the maximum inventory level L is the reorder point Use simulation to investigate an (M,L) inventory system with the following properties: The inventory position is reviewed at the end of each month (fixed review) 1 2 3 4 Backordering is allowed at a cost of $4 per item short each month When an order arrives, it will first be used to relieve the backorder. Lead time is uniformly distributed on the interval [0.25, 1.25]. Beginning inventory is 50 units and there are no orders outstanding. Holding costs are $1 per unit in inventory per month. When an order is placed, its cost is $60 + $5Q where $60 is the ordering cost and $5 is the cost of the item. The time between demands is exponentially distributed with a mean of 1/15 month. The size of demands follows this distribution: Demand Probability 0.5 0.25 0.125 0.125 (a) Create a simulation model to evaluate the above inventory problem. (b) Make ten independent replications, each of run length 100 months preceded by a 12 month initialization period, for the (M, L) = (50, 30) policy. (Hint: Run each individual simulation trial using the "One Trial" worksheet in the Example2.8RefrigInventory spreadsheet.) Record each of the ten independent replication results for average ending inventory, average units ordered per month, and average monthly costs. Adjust worksheet graph as needed to reflect average monthly inventory frequencies. (c) Estimate long-run mean monthly cost with a 95% confidence interval. (d) Using the results of part (a) and (b), estimate the total number of replications needed to estimate mean monthly cost within $4.
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