Application of the Cycles Merging Algorithm to the Shortest Common Superstring Problem

This paper describes the application of the cycles merging algorithm for data compression using an approximate solution to the Shortest Common Superstring (SCS) problem, which is reduced to solving the asymmetric traveling salesman problem to the maximum (MaxTSP). SCS is as follows: given a collection of strings $s_{1},\ldots, s_{m}$, find the shortest string s such that each s_i appears as a substring (a consecutive block) of s. The algorithm is tested for data compression on randomly generated data with the specified parameters, the results are compared with the results of data compression by greedy and 4-approximation algorithms. The efficiency of the CMA algorithm for the maximum problem is investigated.