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Graduate Program in Business Information Systems

Graduate Program in Business Information Systems. Inventory Decisions with Uncertain Factors Aslı Sencer. Uncertainties in real life. Demand is usually uncertain. Probability distributions are used to represent uncertain factors. Ex: Demand is normally distributed OR

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Graduate Program in Business Information Systems

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  1. Graduate Program in Business Information Systems Inventory Decisions with Uncertain Factors Aslı Sencer

  2. Uncertainties in real life • Demand is usually uncertain. • Probability distributions are used to represent uncertain factors. Ex: Demand is normally distributed OR Demand is either 20,30,40 with respective probabilities 0.2, 0.5, 0.3. BIS 517- Aslı Sencer

  3. Stochastic versus Deterministic Models • Mathematical models involving probability are referred to as stochastic models. • Deterministic models are limited in scope since they do not involve uncertain factors. But they are used to develop insight! • Stochastic models are based on “expected values”, i.e. the long run average of all possible outcomes! BIS 517- Aslı Sencer

  4. Example: Drugstore • A drugstore stocks Fortunes.They sell each for $3 and unit cost is $2.10. Unsold copies are returned for $.70 credit. There are four levels of demand possible. How many copies of Fortune should be stocked in October? Payoff Table: BIS 517- Aslı Sencer

  5. Solution: • The expected payoffs are computed for each possible order quantity: Q = 20 Q = 21 Q = 22 Q = 23 $18.00 $18.44 $17.90 $16.79 Optimal stocking level, Q*=21 at an optimal expected profit of $18.44 • If the probabilities were long-run frequencies, then doing so would maximize long-run profit. BIS 517- Aslı Sencer

  6. Example: Drugstore Payoff Table(Figure 16-1) BIS 517- Aslı Sencer

  7. Single-Period Inventory Decision:The Newsvendor Problem • Single period problem (periodic review) • Demand is uncertain (stochastic) • No fixed ordering cost • Instead of h ($/$/period) we have hE($/unit/period=ch) • Instead of p ($/unit) we have pSand pR-c • Q: Order Quantity (decision variable) D: Demand Quantity • Costs: c = Unit procurement cost hE= Additional cost of each item held at end of inventory cycle = unit inventory holding cost-salvage value to the supplier pS= Penalty for each item short (loss of customer goodwill) pR= Selling price BIS 517- Aslı Sencer

  8. Modeling the Newsvendor Problem The objective is to minimize total expected cost, which can be simplified as: where m is the expected demand. BIS 517- Aslı Sencer

  9. Optimal order quantity of the Newsboy Problem Q* is the smallest possible demand such that BIS 517- Aslı Sencer

  10. Example: Newsboy Problem • A newsvendor sells Wall Street Journals. She loses pS= $.02 in future profits each time a customer wants to buy a paper when out of stock. They sell for pR = $.23 and cost c = $.20. Unsold copies cost hE = $.01 to dispose. Demands between 45 and 55 are equally likely. How many should she stock? BIS 517- Aslı Sencer

  11. Example: Solution • Discrete Uniform Distribution Demand is either 45,46,47,..., 55 each with a probability of 1/11. P(D<=Q*)=0.2 Q*=47 units. BIS 517- Aslı Sencer

  12. Newsvendor Problem (Figure 16-3) BIS 517- Aslı Sencer

  13. Multiperiod Inventory Policies • When demand is uncertain, multiperiod inventory might look like this over time. BIS 517- Aslı Sencer

  14. Multiperiod Inventory Policies • The multiperiod decisions involve two variables: • Order quantity Q • Reorder point r • The following parameters apply: • A = mean annual demand rate • k = ordering cost • c = unit procurement cost • ps= cost of short item (no matter how long) • h = annual holding cost per dollar value • = mean lead-time demand BIS 517- Aslı Sencer

  15. Multiperiod Inventory Policies: Discrete Lead-Time Demand • The following is used to compute the expected shortage per inventory cycle: • The following is used to compute the total annual expected cost: BIS 517- Aslı Sencer

  16. Multiperiod Inventory Policies: Discrete Lead-Time Demand • Solution Algorithm. • Calculate the starting order quantity: • Determine the reorder point r*: • Determine optimal order quantity: • This procedure continues –using the last Q to obtain r and r to obtain the next Q- until no values change. BIS 517- Aslı Sencer

  17. Example: Annual demand for printer cartridges costing c = $1.50 is A = 1,500. Ordering cost is k = $5 and holding cost is $.12 per dollar per year. Shortage cost is pS= $.12, no matter how long. Lead-time demand has the following distribution.Find the optimal inventory policy. BIS 517- Aslı Sencer

  18. Example: Solution • The starting order quantity is: r* = 7 cartridges. • B(7) = (8–7)(.03) + (9–7)(.01) + (10–7)(.01)=.08 and the optimal order quantity is: BIS 517- Aslı Sencer

  19. Example: Solution (cont’d.) • Q=290 leads to r=7, so the solution is optimal. The optimal inventory policy is: r* = 7 Q* = 290 • Optimal annual expected cost is: BIS 517- Aslı Sencer

  20. Multiperiod Discrete BackorderingIteration 1 BIS 517- Aslı Sencer

  21. Multiperiod Discrete BackorderingIteration 10 BIS 517- Aslı Sencer

  22. Multiperiod Discrete BackorderingSummary BIS 517- Aslı Sencer

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