ALGORITHMS FOR PROACTIVE INVENTORY MANAGEMENT

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ALGORITHMS FOR PROACTIVE INVENTORY MANAGEMENT

• Algorithm
• A procedure or technique for solving a problem
• Optimization algorithm
• An algorithm which always yields the best
  solution
• Heuristic algorithm
• An algorithm which generally yields a pretty good
  solution
• Lot-sizing algorithms plan production and
  inventory levels in advance based on knowledge of
  future demand

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ALGORITHMS FOR PROACTIVE INVENTORY MANAGEMENT

• Example Product Data
• CS 90 per setup
• Ch 0.50 per unit per period

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LOT FOR LOT

• Simplest lot-sizing rule
• Make as much as you need each period 
• Maximizes total setup cost
• Minimizes total holding cost
•  

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LOT FOR LOT

• Simplest lot-sizing rule
• Make as much as you need each period 
• Maximizes total setup cost
• Minimizes total holding cost
•  

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LOT FOR LOT

• Simplest lot-sizing rule
• Make as much as you need each period 
• Maximizes total setup cost
• Minimizes total holding cost
•  

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LOT FOR LOT

• Simplest lot-sizing rule
• Make as much as you need each period 
• Maximizes total setup cost
• Minimizes total holding cost
•  

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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ECONOMIC ORDER QUANTITY

• A continuous time model applied to discrete
  demand
• Assumes constant and continuous demand
• Use average demand for EOQ formula

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PERIODIC ORDER QUANTITY

• POQ modifies the EOQ for discrete demand
• Assumes a single best reorder interval (number of
  periods covered by a single lot)

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PART-PERIOD BALANCING

• Based upon assumption that total setup and
  holding cost per reorder interval should be equal
• i -- Current period whose lot size is being
  determined
• j -- (j ³ i) Period being considered as final
  period whose demand will be produced in period
  i's production
• dt -- Demand in period t
• Hij -- Total holding cost of producing all demand
  for periods i through j in period i

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PART-PERIOD BALANCING
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PPB ALGORITHM

• Let i be the upcoming period
• Let j i
• Calculate Hij. If j i go to step (4). If
  Hij - Cs gt Hij-1 - Cs go to step (5)
• Let j j 1. Go to step (3)
• Set lot size in period i equal to total demand in
  periods i through j-1.
• Let i j. Go to step (2)
•  

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PPB ALGORITHM

• i 1
• Let j i 1
• H11 0. Since j i, go to step (4).
• 4. Let j j 1 1 1 2. Go to step (3)

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PPB ALGORITHM

• H12 35. Since j ¹ i, continue.
• Is H12 - Cs 35 - 90 55 gt 90 0 - 90
  H11 - Cs ?
• No, so continue
• 4. Let j j 1 2 1 3. Go to step (3)

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PPB ALGORITHM

• H13 75. Since j ¹ i, continue.
• Is H13 - Cs 75 - 90 15 gt 55 35 -
  90 H12 - Cs ?
• No, so continue
• 4. Let j j 1 3 1 4. Go to step (3)

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PPB ALGORITHM

• H14 90. Since j ¹ i, continue.
• Is H14 - Cs 90 - 90 0 gt 15 75 - 90
  H13 - Cs ?
• No, so continue
• 4. Let j j 1 4 1 5. Go to step (3)

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PPB ALGORITHM

• H15 120. Since j ¹ i, continue.
• Is H15 - Cs 120 - 90 30 gt 0 90 - 90
  H14 - Cs ?
• Yes, so go to step (5)
• 5. Set lot size in period i1 equal to total
  demand in periods i1 through j-15-14.

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PPB ALGORITHM

• H15 120. Since j ¹ i, continue.
• Is H15 - Cs 120 - 90 30 gt 0 90 - 90
  H14 - Cs ?
• Yes, so go to step (5)
• 5. Set lot size in period i1 equal to total
  demand in periods i1 through j-15-14.

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PPB ALGORITHM

• H15 120. Since j ¹ i, continue.
• Is H15 - Cs 120 - 90 30 gt 0 90 - 90
  H14 - Cs ?
• Yes, so go to step (5)
• 5. Set lot size in period i1 equal to total
  demand in periods i1 through j-15-14.
• 6. Let i j 5. Go to step (2)

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PPB ALGORITHM

• Final result is the best in this example, but not
  necessarily optimal.