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Int. J. Mol. Sci. 2015, 16(10), 25338-25352; doi:10.3390/ijms161025338

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

1
College of Information, Shanghai Ocean University, Shanghai 201306, China
2
Center for Finance and Accounting Research of University of International Business and Economics, Beijing 100029, China
3
College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
4
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Academic Editor: Mihai V. Putz
Received: 7 September 2015 / Accepted: 8 October 2015 / Published: 23 October 2015
(This article belongs to the Section Physical Chemistry, Theoretical and Computational Chemistry)
View Full-Text   |   Download PDF [767 KB, uploaded 23 October 2015]

Abstract

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. View Full-Text
Keywords: DNA molecules computing; the unbalanced assignment problem; biological optimization algorithm; NP-complete problem DNA molecules computing; the unbalanced assignment problem; biological optimization algorithm; NP-complete problem
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, Z.; Pu, J.; Cao, L.; Tan, J. A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing. Int. J. Mol. Sci. 2015, 16, 25338-25352.

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