Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms - Odili, Julius Beneoluchi; M. N. M., Kahar; Noraziah, Ahmad (IDOSI Publication, 2016)
This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. The three techniques have been applied successfully to solve the popular problem of an anonymous travelling salesman who is searching for the most optimized route to visiting all his customers in different locations of a large city or in a number of cities. This study focusses on these three methods with the aim of ascertaining the most efficient and effective. Results obtained from using these algorithms to solve the benchmark dataset on TSP available in TSPLIB95 serve as the comparative data. The outcome of this experiment shows that the newly-developed African Buffalo Optimization has very encouraging performance in terms of capacity to obtain optimal or near-optimal results consistently and in the most cost-effective manner.