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

被引：19
|
作者：
Wang, Zhaocai [1 ]
Pu, Jun [2 ]
Cao, Liling [3 ]
Tan, Jian [4 ]
机构：
[1] Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China
[2] Univ Int Business & Econ, Ctr Finance & Accounting Res, Beijing 100029, Peoples R China
[3] Shanghai Ocean Univ, Coll Engn Sci & Technol, Shanghai 201306, Peoples R China
[4] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
来源：
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES | 2015年 / 16卷 / 10期
基金：
中国国家自然科学基金;
关键词：
DNA molecules computing; the unbalanced assignment problem; biological optimization algorithm; NP-complete problem; COMPUTATION;
D O I：
10.3390/ijms161025338
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
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.
引用
收藏
页码：25338 / 25352
页数：15
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