A new approach based on PSO algorithm to find good computational encoding sequences

Computational encoding DNA sequence design is one of the most important steps in molecular computation. A lot of research work has been done to design reliable sequence library. A revised method based on the support system developed by Tanaka et al. is proposed here with different criteria to construct fitness function. Then we adapt particle swarm optimization (PSO) algorithm to our encoding problem. By using the new algorithm, a set of sequences with good quality is generated. The result also shows that our PSO-based approach could rapidly converge at the minimum level for an output of the simulation model. The celerity of the algorithm fits our requirements.     

The optimization of DNA encodings based on GA/SA algorithms

The design of DNA sequence plays an important role in improving the reliability of DNA computation. Proper constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. The heuristic improved genetic algorithm (GA)/simulated annealing (SA) algorithm is presented to solve the multi-objective optimize problem, and the DNA sequence design system is developed. Furthermore, an example is illustrated to show the efficiency of our method given here.     

The optimization of DNA encodings based on GA/SA algorithms

The design of DNA sequence plays an important role in improving the reliability of DNA computation. Proper constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. The heuristic improved genetic algorithm (GA)/simulated annealing (SA) algorithm is presented to solve the multi-objective optimize problem, and the DNA sequence design system is developed. Furthermore, an example is illustrated to show the efficiency of our method given here.     

Multi-objective carrier chaotic evolutionary algorithm for DNA sequences design

DNA computing is a new vista of computation, which is of biochemical type. Since each piece of information is encoded in biological sequences, their design is crucial for successful DNA computation. DNA sequence design is involved with a number of design criteria, which is difficult to be solved by the traditional optimization methods. In this paper, the multi-objective carrier chaotic evolution algorithm (MCCEA) is introduced to solve the DNA sequence design problem. By merging the chaotic search base on power function carrier, a set of good DNA sequences are generated. Furthermore, the simulation results show the efficiency of our method.     

Multi-objective carrier chaotic evolutionary algorithm for DNA sequences design

DNA computing is a new vista of computation, which is of biochemical type. Since each piece of information is encoded in biological sequences, their design is crucial for successful DNA computation. DNA sequence design is involved with a number of design criteria, which is difficult to be solved by the traditional optimization methods. In this paper, the multi-objective carrier chaotic evolution algorithm (MCCEA) is introduced to solve the DNA sequence design problem. By merging the chaotic search base on power function carrier, a set of good DNA sequences are generated. Furthermore, the simulation results show the efficiency of our method.     

A membrane evolutionary algorithm for DNA sequence design in DNA computing

DNA sequence design has a crucial role in successful DNA computation,which has been proved to be an NP-hard(non-deterministic polynomial-time hard) problem.In this paper,a membrane evolutionary algorithm is proposed for the DNA sequence design problem.The results of computer experiments are reported,in which the new algorithm is validated and out-performs certain known evolutionary algorithms for the DNA sequence design problem.     

Optimization in the Migration Problem of Mobile Agents in Distributed Information Retrieval Systems

In this paper,we employ genetic algorithms to solve the migration problem (MP).We propose a new encoding scheme to represent trees,which is composed of two parts;the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices.The proposed encoding scheme has the advantages of simplicity for encoding and decoding,ease for GA operations,and better equilibrium between exploration and exploitation.It is also adaptive in that,with few restrictions on the length of code,it can be freely lengthened or shortened according to the characteristics of the problem space.Furthermore,the encoding scheme is highly applicable to the degreeconstrained minimum spanning tree problem because it also contains the degree information of each node.The simulation results demonstrate the higher performance of our algorithm,with fast convergence to the optima or sub-optima on various problem sizes.Comparing with the binary string encoding of vertices,when the problem size is large,our algorithm runs remarkably faster with comparable search capability.     

结合DNA编码的快速混沌图像加密算法

针对现有图像加密算法的加密、解密速度问题,提出了一种与DNA编码相结合的快速图像加密算法,采用新4维混沌系统产生的混沌序列作为索引序列,指明置乱过程中要交换的具体位置.对置乱后的图像进行DNA编码,采用规则1的DNA加法法则和DNA异或法则完成扩散过程后,再用不同的规则进行DNA解码,从而完成二次加密.实验结果表明:本文提出的方法在保证图像加密系统安全的同时,减少了置乱过程中循环遍历的次数,从而提升了加密和解密的速度.     

基于杂草算法的DNA编码序列研究

在DNA自组装过程中,DNA序列的设计是影响DNA组装在可靠性和稳定性问题上的重要因素。为降低DNA组装时出现碱基错误匹配的概率,提出了一种用于DNA序列设计的入侵杂草优化(IWO)算法。采用汉明距离约束、相似度约束、连续性约束、发卡结构约束及解链温度约束建立一个多目标函数优化的数学模型,将DNA序列集设计问题抽象为带有约束条件的多目标优化问题。通过将该算法产生的编码序列和其它两种优化算法产生的序列进行对比分析,证实了该算法的有效性,并拓展了算法在离散空间中的应用。     

Improved taboo search algorithm for designing DNA sequences

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can find a set of good DNA sequences satisfying required constraints.     

Improved taboo search algorithm for designing DNA sequences

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can find a set of good DNA sequences satisfying required constraints.     

基于人工鱼群的DNA编码序列组合优化算法研究

分析DNA编码序列设计的目标及需要满足的约束条件,提出全局人工鱼群算法(GAFSA)生成有效的DNA编码序列.根据优化问题的约束条件及人工鱼群的特点,对人工鱼的视野和步长按进行动态调整.实验结果表明,所述GSFSA算法比遗传算法、多目标进化算法、遗传粒子群算法算法产生的DNA编码序列具有更高的质量.     

路径排序问题基于表面的DNA算法

提出了路径排序问题表面DNA算法三步骤：a．找出两端点的所有链,b．筛选出所有的路,c．得到路序．指出编码问题在DNA计算中的重要性．在算法实现过程中,用保护两端点对应的DNA片段3’端或5’端的办法得到所有的链,并用电泳的方法对链进行排序以及去掉链长大于图权值总和的链;对探针进行生物素标记并且采用观察、记录亮点强度的办法筛选出所有的路;分析实验记录得到路序．将算法推广到最短（长）路问题的不同之处在第三步,即只需分析在表面上排在最前（最后）的DNA链的实验记录就得到最短（长）路．     

A global heuristically search algorithm for DNA encoding

A new efficient algorithm is developed to design DNA words with equal length for DNA computing. The algorithm uses a global heuristic optimizing search approach and converts constraints to a carry number to accelerate the convergence, which can generate a DNA words set satisfying some thermodynamic and combinatorial constraints. Based on the algorithm, a software for DNA words design is developed.     

A global heuristically search algorithm for DNA encoding

A new efficient algorithm is developed to design DNA words with equal length for DNA computing. The algorithm uses a global heuristic optimizing search approach and converts constraints to a carry number to accelerate the convergence, which can generate a DNA words set satisfying some thermodynamic and combinatorial constraints. Based on the algorithm, a software for DNA words design is developed.     

JPEG-LS视频编码的自适应率控制

针对ＪＰＥＧ－ＬＳ算法的编码比特率特性提出了一套编码比特率控制算法。通过此算法可实现固定比特纺的码流传送。控制算法的核心由两部分组成；预编码阶段和后编码阶段。在前一阶段，利用提出的模型推算出满足缓存的估计编码比特数及对应的量化值。     

A new DNA algorithm to solve graph coloring problem

Using a small quantity of DNA molecules and little experimental time to solve complex problems successfully is a goal of DNA computing. Some NP-hard problems have been solved by DNA computing with lower time complexity than conventional computing. However, this advantage often brings higher space complexity and needs a large number of DNA encoding molecules. One example is graph coloring problem. Current DNA algorithms need exponentially increasing DNA encoding strands with the growing of problem size. Here we propose a new DNA algorithm of graph coloring problem based on the proof of four-color theorem. This algorithm has good properties of needing a relatively small number of operations in polynomial time and needing a small number of DNA encoding molecules (we need only 6R DNA encoding molecules if the number of regions in a graph is R).     

A new DNA algorithm to solve graph coloring problem

Using a small quantity of DNA molecules and little experimental time to solve complex problems successfully is a goal of DNA computing. Some NP-hard problems have been solved by DNA computing with lower time complexity than conventional computing. However, this advantage often brings higher space complexity and needs a large number of DNA encoding molecules. One example is graph coloring problem. Current DNA algorithms need exponentially increasing DNA encoding strands with the growing of problem size. Here we propose a new DNA algorithm of graph coloring problem based on the proof of four-color theorem. This algorithm has good properties of needing a relatively small number of operations in polynomial time and needing a small number of DNA encoding molecules (we need only 6R DNA encoding molecules if the number of regions in a graph is R).