GENETIC ALGORITHM APPROACH FOR OPTIMAL CYCLIC TOURROUND THE STATE CAPITALS IN NIGERIA’S NIGER DELTAREGION

The traveling salesman problem (TSP) is a classical simple optimization prob-lem that aims at determining the total distance or cost of visiting (n-1) pointsand returning to the starting point. This research uses the Genetic Algorithm(GA) technique to βind an optimal tour around the nine Niger Delta state capi-tals cities in Nigeria. The partially mapped (PMX) crossover operator and theinversion mutation operator techniques were employed. The method providesan approximated optimal result in time. The data for the research was obtainedthrough an online google map where the distances between the cities and theircoordinates (longitude and latitudes) were obtained. The MATLAB softwarewas used in coding the results show that the BB algorithm yielded an optimaltour of 1351km with a cyclic tour of (X3;1), (X1;9), (X9;6), (X6;8), (X8;4), (X4;7),(X7;5), (X5;2), (X2;3) and then (X3;1) in 9 iteration circles. While the GA with thepopulation size, maximum iteration, crossover probability, and mutation prob-ability set to 30, 10, 0.8, and 0.1 respectively, yielded an optimal path and anoptimal tour 8476125398, that isand 1124.0kms respectively. An improved result was achieved using the GAtechnique.