It is evident that the three goals are not additive. Moreover goals (2) and (3) are
conflicting. Goal programming requests the management to set some achievable
target for each of the objectives and to classify them in the order of significance.
Having obtained this data, goal programming attempts to reduce the deviations from
the set targets. Starting with the most significant goal, the method continues the
process until the accomplishing a less important goal would prevent management
from realising a more important one.
13.3.15 Reliability Theory
Reliability theory deals with quantifying the failure frequency of an item. It
characterises an indicator of quality for a product and its dependence during operations. Component reliability can be defined as the probability that the component
will perform its function (without failure) during a given time period, under specified
environmental conditions. As such, reliability theory involves statistical analysis and
the measurement of failure frequency. When dealing with reliability, the probability
value, the environmental conditions under which successful performance is expected
during a given period, it is essential to specify the minimum acceptable performance
level and the type of necessary maintenance required for the product. Reliability in
infrastructure has been treated in Chaps. 9 and 11.
13.3.16 Markov Analysis
Markov analysis studies the prevalent behaviour of some parameter in order to
predict the future behaviour of that factor. The Russian mathematician Markov first
used the method to study and forecast the behaviour of gaseous particles in a closed
container. In operations research, the method has been effectively applied to a wide
range of situations, such as
(1) the examination of customer behaviour on their brand loyalty and the prediction
of customers changing brands.
(2) the study of newspaper subscriptions
(3) the gradual change in customer behaviour from being a good customer to
becoming a bad debtor.
In all these applications, future behaviour, has been forecast after analysis of
prevalent behaviour.
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367
conflicting. Goal programming requests the management to set some achievable
target for each of the objectives and to classify them in the order of significance.
Having obtained this data, goal programming attempts to reduce the deviations from
the set targets. Starting with the most significant goal, the method continues the
process until the accomplishing a less important goal would prevent management
from realising a more important one.
13.3.15 Reliability Theory
Reliability theory deals with quantifying the failure frequency of an item. It
characterises an indicator of quality for a product and its dependence during operations. Component reliability can be defined as the probability that the component
will perform its function (without failure) during a given time period, under specified
environmental conditions. As such, reliability theory involves statistical analysis and
the measurement of failure frequency. When dealing with reliability, the probability
value, the environmental conditions under which successful performance is expected
during a given period, it is essential to specify the minimum acceptable performance
level and the type of necessary maintenance required for the product. Reliability in
infrastructure has been treated in Chaps. 9 and 11.
13.3.16 Markov Analysis
Markov analysis studies the prevalent behaviour of some parameter in order to
predict the future behaviour of that factor. The Russian mathematician Markov first
used the method to study and forecast the behaviour of gaseous particles in a closed
container. In operations research, the method has been effectively applied to a wide
range of situations, such as
(1) the examination of customer behaviour on their brand loyalty and the prediction
of customers changing brands.
(2) the study of newspaper subscriptions
(3) the gradual change in customer behaviour from being a good customer to
becoming a bad debtor.
In all these applications, future behaviour, has been forecast after analysis of
prevalent behaviour.
13.3 Types of Mathematical Models
367