A comparative study on distance measuring approches for permutation representations

Distance measure plays an important role in permutation problems. Choosing the right distance measure for a given permutation is a biggest challenge. In this paper, we investigates Hamming, Euclidean, Manhattan and Squared Euclidean distance measures for their applicability to various permutation problem. This paper surveys existing distance measures for permutation and present a comparison between them based on application domain, time required to compute, benefits and drawbacks. From the simulation result it is shown that Hamming distance outperform the Euclidean, Manhattan and Squared Euclidean distance measures. This comparison helps the researchers to take quick decision about which distance measure to use for permutation problem. We conclude this work by identifying trends and challenges of research and development towards permutation problem.