A Simple Inventory System



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Transcription:

A Simple Inventory System Section 1.3 Discrete-Event Simulation: A First Course

Section 1.3: A Simple Inventory System customers. demand items.. facility. order items.. supplier Distributes items from current inventory to customers Customer demand is discrete Simple one type of item

Inventory Policy Transaction Reporting Inventory review after each transaction Significant labor may be required Less likely to experience shortage Periodic Inventory Review Inventory review is periodic Items are ordered, if necessary, only at review times (s, S) are the min,max inventory levels, 0 s < S We assume periodic inventory review Search for (s, S) that minimize cost

Conceptual Model Inventory System Costs Holding cost: for items in inventory Shortage cost: for unmet demand Setup cost: fixed cost when order is placed Item cost: per-item order cost Ordering cost: sum of setup and item costs Additional Assumptions Back ordering is possible No delivery lag Initial inventory level is S Terminal inventory level is S

Specification Model Time begins at t = 0 Review times are t = 0, 1, 2,... l i 1 : inventory level at beginning of i th interval o i 1 : amount ordered at time t = i 1, (o i 1 0) d i : demand quantity during i th interval, (d i 0) Inventory at end of interval can be negative

Inventory Level Considerations Inventory level is reviewed at t = i 1 If at least s, no order is placed If less than s, inventory is replenished to S { 0 li 1 s o i 1 = S l i 1 l i 1 < s Items are delivered immediately At end of i th interval, inventory diminished by d i l i = l i 1 + o i 1 d i

Time Evolution of Inventory Level Algorithm 1.3.1 l 0 = S; /* the initial inventory level is S */ i = 0; while (more demand to process ) { i++; if (l i 1 < s) o i 1 = S - l i 1 ; else o i 1 = 0; d i = GetDemand(); l i = l i 1 + o i 1 - d i ; } n = i; o n = S - l n ; l n = S; /* the terminal inventory level is S */ return l 1,l 2,...,l n and o 1,o 2,...,o n ;

Example 1.3.1: SIS with Sample Demands Let (s, S) = (20, 60) and consider n = 12 time intervals i : 1 2 3 4 5 6 7 8 9 10 11 12 d i : 30 15 25 15 45 30 25 15 20 35 20 30 l i 80 S 40 s 0 20 40 0 1 2 3 4 5 6 7 8 9 10 11 12 i

Output Statistics What statistics to compute? Average demand and average order d = 1 n n i=1 d i ō = 1 n n o i. i=1 For Example 1.3.1 data d = ō = 305/12 25.42 items per time interval

Flow Balance A Simple Inventory System Average demand and order must be equal Ending inventory level is S Over the simulated period, all demand is satisfied Average flow of items in equals average flow of items out customers. d facility. ō supplier The inventory system is flow balanced

Constant Demand Rate Holding and shortage costs are proportional to time-averaged inventory levels Must know inventory level for all t Assume the demand rate is constant between review times l(t) 80 S 40 s 0 20 40..... t 0 1 2 3 4 5 6 7 8 9 10 11 12

Inventory Level as a Function of Time The inventory level at any time t in i th interval is l(t) = l i 1 (t i + 1)d i if demand rate is constant between review times l i 1 (i 1, l i 1 ) l(t) l i 1 d i l(t) = l i 1 (t i + 1)d i (i, l i 1 d i). i 1 l i 1 = l i 1 + o i 1 represents inventory level after review i t

Inventory Decrease Is Not Linear Inventory level at any time t is an integer l(t) should be rounded to an integer value l(t) is a stair-step, rather than linear, function l(t) l i 1 l i 1 d i (i 1, l i 1 ) l(t) = l i 1 (t i + 1)d i + 0.5 (i, l i 1 d i). i 1 i t

Time-Averaged Inventory Level l(t) is the basis for computing the time-averaged inventory level Case 1: If l(t) remains non-negative over i th interval i l + i = l(t)dt i 1 Case 2: If l(t) becomes negative at some time τ τ l + i = l(t)dt i 1 l i i = l(t)dt τ l + i l i is the time-averaged holding level is the time-averaged shortage level

Case 1: No Back Ordering No shortage during i th time interval iff. d i l i 1 i 1 i 0 l i 1 d i l i 1 l(t) t. (i 1, l i 1 ) (i, l i 1 d i) Time-averaged holding level: area of a trapezoid l + i = i i 1 l(t)dt = l i 1 + (l i 1 d i) 2 = l i 1 1 2 d i

Case 2: Back Ordering Inventory becomes negative iff. d i > l i 1 i 1 τ i l i 1 d i 0 s l i 1 l(t) t. (i 1, l i 1 ) (i, l i 1 d i)

Case 2: Back Ordering (Cont.) l(t) becomes negative at time t = τ = i 1 + (l i 1 /d i) Time-averaged holding and shortage levels for i th interval computed as the areas of triangles l i τ l + i = i 1 i = τ l(t)dt = = (l i 1 )2 2d i l(t)dt = = (d i l i 1 )2 2d i

Time-Averaged Inventory Level Time-averaged holding level and time-averaged shortage level l + = 1 n n i=1 l + i l = 1 n n i=1 l i Note that time-averaged shortage level is positive The time-averaged inventory level is l = 1 n n 0 l(t)dt = l + l

Computational Model sis1 is a trace-driven computational model of the SIS Computes the statistics d, ō, l +, l and the order frequency ū ū = number of orders n Consistency check: compute ō and d separately, then compare

Example 1.3.4: Executing sis1 Trace file sis1.dat contains data for n = 100 time intervals With (s, S) = (20, 80) ō = d = 29.29 ū = 0.39 l + = 42.40 l = 0.25 After Chapter 2, we will generate data randomly (no trace file)

Operating Costs A facility s cost of operation is determined by: c item : unit cost of new item c setup : fixed cost for placing an order c hold : cost to hold one item for one time interval c short : cost of being short one item for one time interval

Case Study A Simple Inventory System Automobile dealership that uses weekly periodic inventory review The facility is the showroom and surrounding areas The items are new cars The supplier is the car manufacturer...customers are people convinced by clever advertising that their lives will be improved significantly if they purchase a new car from this dealer. (S. Park) Simple (one type of car) inventory system

Example 1.3.5: Case Study Materialized Limited to a maximum of S = 80 cars Inventory reviewed every Monday If inventory falls below s = 20, order cars sufficient to restore to S For now, ignore delivery lag Costs: Item cost is c item = $8000 per item Setup cost is c setup = $1000 Holding cost is c hold = $25 per week Shortage cost is c hold = $700 per week

Per-Interval Average Operating Costs The average operating costs per time interval are item cost: c item ō setup cost: c setup ū holding cost: c hold l + shortage cost: c short l The average total operating cost per time interval is their sum For the stats and costs of the hypothetical dealership: item cost: $8000 29.29 = $234, 320 per week setup cost: $1000 0.39 = $390 per week holding cost: $25 42.40 = $1, 060 per week shortage cost: $700 0.25 = $175 per week

Cost Minimization By varying s (and possibly S), an optimal policy can be determined Optimal minimum average cost Note that ō = d, and d depends only on the demands Hence, item cost is independent of (s, S) Average dependent cost is avg setup cost + avg holding cost + avg shortage cost

Experimentation Let S be fixed, and let the demand sequence be fixed If s is systematically increased, we expect: average setup cost and holding cost will increase as s increases average shortage cost will decrease as s increases average dependent cost will have U shape, yielding an optimum From results (next slide), minimum cost is $1550 at s = 22

Example 1.3.7: Simulation Results 600 500 400 300 200 100 0 1400 1300 1200 1100 1000 900 800 setup cost s 0 5 10 15 20 25 30 35 40 holding cost s 0 5 10 15 20 25 30 35 40 600 500 400 300 200 100 0 2000 1900 1800 1700 1600 1500 1400 0 5 10 15 20 25 30 35 40 shortage cost total cost s s 0 5 10 15 20 25 30 35 40