Rent-a-Car example model serves the sole purpose of
illustrating the basic knowledge representation concepts of
Pro/3. The Rent-a-Car model is a very simple financial analysis
type of model. The essential goal is to determine the net present
value of a car rental business under two different market share
assumptions (for a period of 12 months). The Rent-a-Car model does not
use certainty rules. The Rent-a-Car model consists of one database
file RAC.3KB with 27 sentence types. The model is NOT an introduction
to Pro/3 knowledge modeling, but rather a reference for this
introduction (Introduction
to knowledge modeling with Pro/3).
Factual
Knowledge
The Rent-a-Car business derives its income from renting out
(on a monthly basis) two fleets of cars (cars and vans). There
are some fixed and variable expenditures besides the servicing of
a loan. The car fleet exists sentences
define data of the two vehicle fleets (cars and vans). Fixed
monthly costs and monthly net rental revenues are specified per
vehicle. The fixed costs occur whether or not the vehicle is
rented out. Note that "car" sometimes is used
generically to mean both cars and vans.
The loan exists sentence
defines the loan liability:
The business scenario exists sentences
define the two business scenarios, that is, Rent-a-car's assumed
market share for cars and vans.
The projection
period is assumed sentence defines the length of the
analysis period.
The market size is known sentences define the
known market sizes for the two vehicle
classes during the calendar year: (in NL format):
market data with no of rentals 140, vehicle class CAR and period 1 is known!
market data with no of rentals 170, vehicle class CAR and period 2 is known!
market data with no of rentals 190, vehicle class CAR and period 3 is known!
market data with no of rentals 210, vehicle class CAR and period 4 is known!
market data with no of rentals 220, vehicle class CAR and period 5 is known!
market data with no of rentals 250, vehicle class CAR and period 6 is known!
market data with no of rentals 350, vehicle class CAR and period 7 is known!
market data with no of rentals 300, vehicle class CAR and period 8 is known!
market data with no of rentals 180, vehicle class CAR and period 10 is known!
market data with no of rentals 140, vehicle class CAR and period 11 is known!
market data with no of rentals 180, vehicle class CAR and period 12 is known!
market data with no of rentals 60, vehicle class VAN and period 1 is known!
market data with no of rentals 100, vehicle class VAN and period 3 is known!
market data with no of rentals 250, vehicle class VAN and period 6 is known!
market data with no of rentals 350, vehicle class VAN and period 7 is known!
market data with no of rentals 300, vehicle class VAN and period 8 is known!
market data with no of rentals 130, vehicle class VAN and period 9 is known!
market data with no of rentals 100, vehicle class VAN and period 10 is known!
Rules
The rules in the Rent-a-car model are
stored in nine realms: MARKET, CASHFLOW, CHARGES, CONCLUD, CONDPRO,
ENERAL, INC-EXP, LOAN, RENTAL and SUMMARY. A few notes:
- the predicate is projected is used for various projections made
without reference to one of the two business scenarios,
i.e. projections which apply to both scenarios
- the predicate is
conditionally projected is used for
projections which are particular to a given business
scenario
The CONDPRO rule states that anything
that is projected also can be regarded as conditionally
projected for either of the scenarios.
Assumed market size
The known market data
are somewhat incomplete i.e. assumptions for some periods are missing. The
MARKET rule defines how the incomplete data are made complete (with respect to
assumptions for each period), through interpolation.
Operations revenue and expense rules
The operations revenue and expense rules are stored in RENTAL- and INC-EXP realms. The first
INC-EXP-rule (simple implication rule)
defines how projected expense cash flows are derived from the
fixed monthly costs of the existing car fleets. The second
INC-EXP-rule (simple implication rule) defines how conditionally
projected revenue cash flows (i.e. care rental revenues), are
derived from conditionally projected car rentals and the monthly
net rental revenues of the existing car fleets. The third
INC-EXP-rule (simple implication rule) defines Rent-a-car's fixed
monthly costs (salaries and rent).
The RENTAL-rule (simple implication rule) defines how
conditionally projected car rentals are derived from the existing
car fleets, the market share and market size assumptions. The
function market slice computes Rent-a-car's potential slice (in
terms of no of rentals) of the car/van markets (given vehicle
class, period and scenario no). The actual slice is the lesser of
the potential market slice and the number of vehicles in the
fleet.
Loan repayment and interest
The first LOAN-rule (simple implication rule) derives projected
(loan-)repayments from the existing loan. The second LOAN-rule (accumulation rule) derives
projected accumulated repayments from projected repayments. The
third LOAN-rule (simple implication rule) derives the projected
interest payments from the existing loan (which states the
starting balance and the interest rate) and the accumulated
repayments (which defines the total amount repaid at the end of
each month). Interest is based on the starting balance of each
month.
Bank charges
The CHARGES-rule (simple implication rule) defines how
conditionally projected bank charges are derived from
conditionally projected expense cash flows, interest payments and
repayments. The rule simply defines the bank charges as 10 per
such cash flow.
Cash flows
The GENERAL-rule (generalization rule)
defines that conditionally projected cash flows are
generalizations of conditionally projected expense cash flows,
revenue cash flows, (loan-)repayments, interest payments and bank
charges. The four CASHFLOW rules subsequently derive from the cash flow is conditionally projected
sentences: conditionally projected net cash flows, net discounted
cash flows, net present value and cash balances.
Conclusions and summaries
The four CONCLUD-rules derive different conclusions regarding
the projected utilization of the car fleets. The SUMMARY-rule
derives the ultimate conclusion of the projections, namely the
net present value of the two business scenarios. The following two sentences
represent the "final" derivation of the model:
The NPV figures used be different in
older version of the RAC-model.
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