Page 12 - DCOM303_DMGT504_OPERATION_RESEARCH

Unit 1: Introduction to Operations Research

maximize net collections over multiple billing periods. GE developed a probabilistic Notes
account flow model and statistically designed programmes to provide accurate data on
collection resource performance. A linear programming formulation produces optimal
resource allocations that have been implemented across the business.
 Control of the water distribution system under Irrigation scheme in Malaysia: A linear
programming optimizations model was developed and adapted for daily operating
decisions that would provide for a proper control of the water distribution system in real-
time for a Irrigation scheme in Malaysia. Water orders are used as input in the optimizations
model and the water ordering programme employs a simplified routing method to obtain
a solution to the unsteady state condition. The routed flow is then optimized by minimizing
the deviation between gate releases and water order demands of the users using the linear
programming technique. Physical limitations of the system and water volume balance
are used as constraints.

The results showed that the model is capable of providing the desired operating plan with
a more stable flows and manageable releases. By following the models predictions, all the
gate demands are met while stable flows in canal reaches are maintained and canal water
depths are kept within the desired target levels.

 Formulating insurance polices by Life Insurance Company in India: LIC uses OR to decide
on the premium rate for it’s various policies and also how best the profits could be
distributed in the case of profit policies.

 Application of OR for optimum utilization of urban facilities: Increasingly, citizens are
demanding more urban services, by type, quantity, and quality. The resulting pressure,
between the demands for more and better services, on the one hand, and decreased revenue,
on the other, has created a strong need for improved management decision making in
urban services.
Thus, OR is widely used for effective and efficient allocation or deployment of the resources
of urban service systems, including personnel, equipment, and various service-improving
technologies.
An important consequence of the application of OR to a wide variety of problems is that a small
set of problem types has been identified which accounts for most problems. Because of the
frequent recurrence of these problems, prototype techniques have been developed for modeling
them and for deriving solutions from these models. Prototype applications include:
Forecasting: Using time series analysis to answer typical questions such as, how big will demand
for products be? What are the sales patterns? How will this affect profits?

Finance & Investment: How much capital do we need? Where can we get this? How much will
it cost?
Manpower Planning & Assignment: How many employees do we need? What skills should they
have? How long will they stay with us?
Sequencing & Scheduling: What job is most important? In what order should we do jobs?
Location, Allocation, Distribution & Transportation: Where is the best location for operation?
How big should facilities be? What resources are needed? Are there shortages? How can we set
priorities?

Reliability & Replacement Policy: How well is equipment working? How reliable is it? When
should we replace it?
Inventory Control and Stock out: How much stock should we hold? When do we order more?
How much should we order?

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