An optimal investment policy for two firms in Kumasi

dc.contributor.authorTwum, Stephen B.
dc.date.accessioned2012-03-27T22:01:41Z
dc.date.accessioned2023-04-20T01:28:17Z
dc.date.available2012-03-27T22:01:41Z
dc.date.available2023-04-20T01:28:17Z
dc.date.issued1994-08-27
dc.descriptionA thesis submitted to the Board of Postgraduate Studies, Kwame Nkrumah University of Science and Technology, Kumasi, in partial fulfilment of the requirement for the award of the Degree of Master of Science in Mathematics, 1994en_US
dc.description.abstractThe focus of this thesis has been to look at one of the widely applied and effective modeling tools of Operations Research known as Linear programming, and how it is applied to an investment decision problem of two Firms in Kumasi. The separate investment problems of the two firms are first modeled as a linear programming problem and solved. A joint investment problem is afterwards simulated and modeled into a linear programming problem which is then solved, a step taken to see whether the two firms stand to gain operating together. A sensitivity analysis is performed on the three investment models formulated. This is done to see how the solutions react to slight variations of some chosen parameters of the models, after which the best solutions to the three models are selected. Finally recommendations are made for an optimum investment policy for the two firms separately and jointly.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/3320
dc.language.isoenen_US
dc.relation.ispartofseries2095;
dc.titleAn optimal investment policy for two firms in Kumasien_US
dc.typeThesisen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
KNUST Library.pdf
Size:
7.09 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.73 KB
Format:
Item-specific license agreed to upon submission
Description:
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Collections