It seems cleverer to look into any TSP first by learning from its historical background in order to grab the fundamentals of the task usually required in such kind of exercises. TSP problems are described shortly as easy model to understand but actually hard in solving process. Thus, simply remember that TSP under the category of [problem having more to do with the called hard-problems; they are non-polynomial based problems (i.e. No polynomial time algorithms known) in most cases. In fact, TSP initially (1800-1832) did not involve math concepts. However, despite the scarcity of direct algorithms for such TSP situations, there are still ways to solve the problem of course not to its exact required solutions but, to the (nearer/most) acceptable level. This solving process is about finding some approximation methods and the solution series labelled optimization, which are both more subject to human understanding than the machines’ one, hence the need for heuristic decision in regular and hard problems. Therefore, the papers review in this article is about analysing through TSP exploration, the general algorithms or standard methods, then attempting to classify the use of each relatively to TSP domains of application, mainly based on the research literatures.