A Biogeography-Based Optimization with a Greedy Randomized Adaptive Search Procedure and the 2-Opt Algorithm for the Traveling Salesman Problem

We develop a novel method to improve biogeography-based optimization (BBO) for solving the traveling salesman problem (TSP). The improved is comprised of greedy randomized adaptive search procedure, 2-opt algorithm, and G2BBO. G2BBO formulation derived process flowchart shown in this article. For TSP, effectively avoids local minimum accelerates convergence by optimizing initial values. To demonstrate, we adopt three public datasets (eil51, eil76, kroa100) from TSPLIB compare them with various well-known algorithms. results as well other algorithms perform close enough optimal solutions eil51 eil76 where simple TSP coordinates are considered. In case kroa100, more complicated coordinates, shows greater performance over methods.