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|Title: ||Optimal Campaign Visitation of Presidential Aspirants Case Study: Ashanti Region of Ghana|
|Authors: ||Ansah, Maxwell Owusu|
|Issue Date: ||11-Aug-2008|
|Series/Report no.: ||4970;|
|Abstract: ||The campaign to be flag bearers for political parties for presidential election leave campaign teams wondering how to travel to all the constituencies and plan such visits with minimum cost Most of the cost incurred is by way of transportation and minimizing the distances covered in such trips goes a long way to bring down cost, since transportation costs depend on distances traveled.
In this research the itinerary of the aspirant was tackled as a Traveling Salesman ¥ Problem (TSP) with simulated annealing (SA) used to find the global minimum of the of the distances traveled. The Ashanti Region of Ghana with thirty nine constituencies was used as a case study for the research. The relevant literature was reviewed. In the development of the algorithm, real road lengths were used instead of the norm-1 distances which are widely accepted for the solution of the TSP using SA. This was because in the real world situation, the norm-1 is of little use since most of the* campaign travels are done by road and not by air or other means. A heuristic algorithm, based on a matrix of distances connecting these constituencies, was developed and used successfully to find the optimal traveling distance for the thirty nine constituencies in the Ashanti Region of Ghana and the optimal distance found to be 818.6km. This optimal solution was obtained after a number of iterations, which lasted 1200 sec on the average when using a Hewlett Packard laptop with a 2.00GB processor
Recommendations were given for the research to be extended to the two hundred and thirty constituencies across the country and for the inclusion of some constraints as road class and river bodies.|
|Description: ||A thesis submitted to the board of Graduate Studies in partial fulfillment of the requirement for the award of the degree of Master of Science (MSc) Industrial Mathematics, 2008|
|Appears in Collections:||Distance Learning|
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