Paper Type

Master's Thesis


College of Computing, Engineering & Construction

Degree Name

Master of Science in Computer and Information Sciences (MS)



NACO controlled Corporate Body

University of North Florida. School of Computing

First Advisor

Dr. Asai Asaithambi

Second Advisor

Dr. Swapnoneel Roy

Third Advisor

Dr. Xudong Liu

Department Chair

Dr. Sherif Elfayoumy

College Dean

Dr. William F Klostermeyer


Genome rearrangement problems in computational biology [19, 29, 27] and zoning algorithms in optical character recognition [14, 4] have been modeled as combinatorial optimization problems related to the familiar problem of sorting, namely transforming arbitrary permutations to the identity permutation. The term permutation is used for an arbitrary arrangement of the integers 1, 2,···, n, and the term identity permutation for the arrangement of 1, 2,···, n in increasing order. When a permutation is viewed as the string of integers from 1 through n, any substring in it that is also a substring in the identity permutation will be called a strip. The objective in the combinatorial optimization problems arising from the applications is to obtain the identity permutation from an arbitrary permutation in the least number of a particular chosen strip operation. Among the strip operations which have been investigated thus far in the literature are strip moves, transpositions, reversals, and block interchanges [16, 2, 25, 11, 34]. However, it is important to note that most of the existing research on sorting by strip operations has been focused on obtaining hardness results or designing approximation algorithms, with little work carried out thus far on the implementation of the proposed approximation algorithms. This research starts with implementing two existing algorithms [5, 34] and as the main contributions, provides two new algorithms for sorting by strip swaps: 1) A greedy algorithm in which each strip swap reduces the number of strips the most, and puts maximum strips in their correct positions; 2) Another algorithm that uses the strategy of bringing closest consecutive pairs together called the closest consecutive pair (CCP) algorithm. The approximation ratios for the implemented algorithms are also experimentally estimated.