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A New Efficient Algorithm for the All Sorting Reversals Problem with No Bad Components.

Biing-Feng Wang

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|September 10, 2015

Summary

This summary is machine-generated.

This study presents a new algorithm for the all sorting reversals (ASR) problem without bad components. The algorithm achieves O(n^2) worst-case time complexity, improving practical performance for permutation sorting.

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Area of Science:

Computational Biology
Bioinformatics
Algorithms

Background:

The all sorting reversals (ASR) problem seeks reversals to advance permutations towards a target.
Previous algorithms by Siepel (O(n^3)) and Swenson et al. (O(n^2)) faced limitations, particularly with 'bad components'.

Purpose of the Study:

To develop an efficient and reliable algorithm for the ASR problem, specifically addressing instances without 'bad components'.

Main Methods:

A novel algorithm is introduced for the ASR problem, focusing on permutations lacking 'bad components'.
The algorithm's time complexity is analyzed in worst-case and practical scenarios.

Main Results:

The new algorithm demonstrates an O(n^2) worst-case time complexity.
In practice, the algorithm exhibits linear time complexity relative to input and output size.

Conclusions:

This research offers a practical and efficient solution for the ASR problem without 'bad components'.
The algorithm provides a significant improvement over existing methods, especially for common data types.