الفهرس 
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Abstract
Inventories of different types play an important role in determining the
operating efficiency of organizations. They do exist in industry as well as
in service establishments, and act as an integral part of the organization.
They support production, sales, and other main functions of the
enterprise.
With the advance of business nature, in both size and type, the problem
on inventory becomes more complex and requires different tools to
handle it. Numerous research works have been presented since the turn
of the last century.
Basically there are two elements of inventory which have been
thoroughly investigated, namely the order quantity and the lead-time.
Traditionally, inventory models are classified into two main categories:
stochastic models and deterministic models.
Stochastic models are more complex and messy in modeling and the
methods of solving. Nevertheless, they describe the real situation with
higher accuracy. Mathematical modeling presents an important phase in
describing stochastic inventory situations. Objectives are concentrated on
obtaining optimal or quasi-optimal solutions for order quantity. In many
cases, mathematical modeling stops short of describing the case specially
if it has wide ramification. In this case, the only effective tool available is
simulation techniques.
This thesis reviews the problem of inventory and the work presented in
the field. It applies the concept of system dynamics on a lubricating-oil
marketing company to simulate the effect of varying orders on the system
of inventories. System dynamics is a powerful approach to handle
complex situations like that of the” case under consideration. This case
consists of empty packages sub-system, bulk material sub-system, filling
plant sub-system, and distributor sub-system.
A model uses the concept ofPowersim, which is a simulation package
suitably applied in dynamic situations, to describe the interrelationships
between the different elements in the sub-systems of the case.
The model presented in this thesis is tested using a standard run and a
planned experimental test. Tests are related to varying orders, lead-times,
process delays, information delays and inventory coverage periods.