Lab # 6: Designing INVENTORY System
SSUET/QR/114
LAB # 6
DESIGNING INVENTORY SYSTEM
OBJECTIVE
The SIGMA Model, INVENTRY.MOD, is a discrete event simulation. It models
RETROSPECTIVE OPTIMAL INVENTORY CYCLE MANAGEMENT.
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Lab # 6: Designing INVENTORY System
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THEORY
I. STATE VARIABLE DEFINITIONS.
For this simulation, the following state variables are defined:
H: UNIT-TIME HOLDING COST (real valued)
K: FIXED ORDERING COST (real valued)
D: POISSON DEMAND RATE (real valued)
L: EXPECTED LEAD TIME (NORMAL) (real valued)
Q: OPTIMAL ORDER QUANTITY FOR EACH CYCLE (integer valued)
R: OPTIMAL REORDER POINT FOR EACH CYCLE (integer valued)
N[256]: TIMES THAT DEMANDS ARRIVE DURING CYCLE (real valued)
H_COST: CUMULATIVE HOLDING COSTS TO MEET CYCLE DEMAND (real
valued)
T: THE COUNT OF DEMAND ARRIVALS (integer valued)
NT: LEAD TIME WHEN ORDER SHOULD HAVE BEEN PLACED (real valued)
CYCLE: TIME DURATION OF INVENTORY CYCLE (real valued)
II. EVENT DEFINITIONS.
Simulation state changes are represented by event vertices (nodes or balls)
in a SIGMA graph. Event vertex parameters, if any, are given in parentheses.
Logical and dynamic relationships between pairs of events are represented
in a SIGMA graph by edges (arrows) between event vertices. Unless otherwise
stated, vertex execution priorities, to break time ties, are equal to 5.
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Lab # 6: Designing INVENTORY System
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1. The RUN(H,K,D,L) event occurs when START OF THE RUN.
Initial values for, H,K,D,L, are needed for each run.
After every occurrence of the RUN event:
Unconditionally, SCHEDULE THE FIRST DEMAND;
that is, schedule the SALE(T) event to occur in (1/D)*ERL{1}
time units...using the parameter value(s) of 1.
2. The SALE(T) event occurs when SALES OF AN ITEM FROM INVENTORY.
This event causes the following state change(s):
H_COST=H_COST+H*CLK
N[T]=CLK
After every occurrence of the SALE event:
If H_COST<K, then SCHEDULE THE NEXT DEMAND;
that is, schedule the SALE(T) event to occur in (1/D)*ERL{1}
time units...using the parameter value(s) of T+1.
If H_COST>=K, then THE BREAK-EVEN POINT HAS BEEN REACHED;
that is, schedule the ORDER() event to occur without
delay.
(Time ties are broken by an execution priority of 4.)
3. The ORDER() event occurs when APPROXIMATE EQUAL-COST ORDER
QUANTITY.
This event causes the following state change(s):
Q=T-1
CYCLE=N[Q]
L=NOR{L;.1*L}
After every occurrence of the ORDER event:
Unconditionally, USE THE LEAD TIME TO FIND THE REORDER POINT;
that is, schedule the REORD(T) event to occur without
delay...using the parameter value(s) of 1.
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Lab # 6: Designing INVENTORY System
4. The REORD(T)
COMPUTATION.
event
SSUET/QR/114
occurs
when
OPTIMAL
REORDER
POINT
This event causes the following state change(s):
NT=(CYCLE-N[Q-T])
After every occurrence of the REORD event:
If (T<Q) and (NT<=L), then ITERATE THROUGH THE CUMULATIVE
DEMAND TO FIND R;
that is, schedule the REORD(T) event to occur without
delay...using the parameter value(s) of T+1.
If (NT>L) and (T<Q), then THE REORDER POINT IS FOUND, STOP THE
CYCLE;
that is, schedule the STOP() event to occur without
delay.
(Time ties are broken by an execution priority of 4.)
If T>=Q, then schedule the ERROR() event to occur without
delay.
5. The STOP() event occurs when END OF THE REPLENISHMENT CYCLE.
This event causes the following state change(s):
R=T
After every occurrence of the STOP event:
Unconditionally, INITIALIZE AND START RUNNING THE NEXT CYCLE;
that is, schedule the RUN(H,K,D,L) event to occur without
delay...using the parameter value(s) of 2,30,10,.5.
(Time ties are broken by an execution priority of 2.)
If SET{RND*32000}, then THIS CYCLE IS DONE, DO NOT STOP AGAIN!;
that is, immediately cancel the next scheduled occurrence
of the STOP event.
6. The ERROR() event occurs when OCCURRENCE OF A LEAD-TIME GREATER
THAN CYCLE.
No additional events are scheduled here.
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Lab # 6: Designing INVENTORY System
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ASSIGNMENT
Study the above simulation in detail and draw a real life simulation.
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