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Essay / Research Paper Abstract
This 4 page paper examines a question supplied by the student, there are a number of auditors and a number of firms, each auditor has to visit each firm for the period of a month. Using statistical analysis the paper shows the student how the allocation of the auditor to the firm might take place. The bibliography cites 3 sources.
Page Count:
4 pages (~225 words per page)
File: TS14_TEauditques.rtf
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Unformatted sample text from the term paper:
auditor each month. The firm need to change the auditor to each company each month. The auditors live a long way from each firm and the company will need to
assess the best route for each auditor in order to maximise the use of their resources. The data given is in a table with only the distance of each auditor
from each firm, there is no interrelated data and no geographical indications of direction. There are several approaches we could take to resolving this type of problem with the
sue of statistical analysis. The first is with the use of linear programming. Linear programming is used where there is the need for a procedure to allocate a scare or
limited resource to different activities. Here the resource is the time of the auditor and the activities are the auditing of the companies. This is a potent tool and is
widely used in many different areas such as government and business. The aim is to gain the optimum production or supply mix, here the optimum depends on location and location
of the resources to the firms (Curwin and Slater, 2001). There are two main approaches seen when using linear programming, the first
is to maximise the benefits of resources, the second is to minimise the costs when meeting the set criteria, it is this latter that is relevant for this case as
the further the auditor has to travel the higher the relevant cost in travel and also in lost time (Curwin and Slater, 2001).
To use linear programming there need to be three characteristics present, there has to be a linear objective function, There need to be a set of linear constraints and there
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