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The Traveling Salesman Problem (TSP) is an NP-hard problem that has been used as a significant testing ground for many algorithms. It is also a problem that appears in many real industrial problems. This paper describes a Bee Colony Optimization (BCO) algorithm with a fragmentation state transition rule (FSTR) for TSP. The FSTR in the BCO algorithm helps bees to produce a tour by combining a few fragments of cities. Previously in [1, 2], the authors suggest that bees have to travel from one city to another city in order to build a complete tour. This is a time consuming process. With the help of the FSTR, the BCO algorithm is tested on 84 benchmark problems with the dimension of [14, 1379]. The results show that while the average solution quality is 0.11% from known optimum, the computational time is reduced by 50.45%.