一类来自有限域 GF（16）子群上的高码率的 LDPC码

最近,Sobhani等人利用在有限群上的元素置换方法构造群置换LDPC码,本文在此基础上,给出了一类在有限域GF（16）的子群上构造的高码率的LDPC码,其Tanner图围长至少为8。仿真结果表明,这类码执行性能优于相应类型的随机LDPC码和其代数结构的准循环LDPC码。     

太阳能风能互补储能发电系统容量优化算法

随着互补型储能发电系统日益普及,其覆盖范围也不断扩大,但容量优化技术仍处于单一能源阶段。为此,针对太阳能风能互补储能发电系统,设计了一种容量优化算法。通过分析发电系统的电能输出情况,获得其年产出与供应状态,然后根据电能均衡准则构建容量优化目标及约束条件。然后结合差分进化算法进行变异、交叉和选择等操作,再通过粒子群算法更新方位与速度,二者结合取得亲体与群体的当前最优解,经迭代循环实现储能系统容量优化。经实验研究分析,并通过对组件配置量、负荷缺电率等数据发现,该算法在大幅提升经济效益的同时,确保了供电可靠性,表明该算法具有显著的优化优越性与较大的试运行潜力。     

一个加强的Hilbert型不等式

本文应用权系数方法及Euler-Maclaurin求和公式,建立一个加强的Hilbert型不等式,并考虑了最佳常数因子联系参数的等价陈述.     

基于模拟退火与改进粒子群的矿井通风优化算法

建立以矿井通风网络总功率最小为目标的非线性优化数学模型,改进粒子群优化算法实现寻忧.在粒子群算法中引入变异操作,提出了一种新的惯性权重,并构造一种新的粒子选择方法控制违反约束条件的粒子数量,提高粒子群算法寻找边界的能力.将风量平衡定律和风压平衡定律的约束条件转化为目标函数的惩罚项,改进粒子群(Improved Part...     

预应力群锚体系施工中的技术问题与应对措施

随着我国建设的快速发展,预应力群锚体系得到了广泛的应用,本文针对预应力群锚体系施工中的技术问题与应对措施进行分析。     

Operational Patterns of Industrial Symbiosis Network in Industrial Cluster District Based on Circular Economy Theory

Industrial symbiosis network （ISN） is an efficient organizational form for improving resource recycling and efficiency in industrial cluster district. Because of the variety of industrial cluster district formation model, the industrial symbiosis network is different with each other. Based on the circular economy theory, combing with international tendency of cluster district, the paper puts forward the relying-on-oriented industrial symbiosis network. Meanwhile, it also analyzes its organizational mechanism, operating pattern and environmental performance. Through the above efforts, we hope it could be helpful for industry cluster district sustainable development in China.     

基于DPSO的无等待混合流水车间调度方法

研究了无等待混合流水车间调度问题,调度目标为最小化工件的最大完成时间。针对问题中工件加工无等待特点,设计了分阶段实现的无等待算法,并将机器的能力约束嵌入到算法之中。在此基础上,首次应用离散粒子群优化算法对无等待混合流水车间调度问题进行了优化求解。通过仿真实验表明,离散粒子群算法的优化质量优于遗传算法及LTPT、STPT和FCFP三种启发式算法,同时验证了分阶段无等待算法的有效性。

Abstract：

A no-wait hybrid flow shop（NWHFS） scheduling problem was studied for the objective of minimizing makespan.For the no-wait constraint between two sequential operations of a job,not only the no-wait algorithm of grading was designed,but also the number restriction of machines was embedded into this algorithm.On this basis,the discrete particle swarm optimization（DPSO） algorithm was proposed for the first time to solve such problems.The last simulation experiments show the optimization qualities of DPSO are superior to those of the genetic algorithm（GA） and the heuristic algorithms of LTPT,STPT and FCFP,and demonstrate the effectiveness of the no-wait algorithm of grading as well.     

基于动态种群结构的粒子群算法及仿真研究

针对标准粒子群算法易陷入局部最优而早熟的问题,提出了一种基于动态种群结构的粒子群算法。该算法在种群结构中引入小世界网络模型,由于网络模型的演化,使算法具有动态的种群结构,从而保持了种群的多样性。同时为了使粒子尽可能地分布在不同的搜索空间,在网络模型演化过程中考虑了结点的个体价值。为了加快算法的收敛速度,在进化后期采用全局模型粒子群算法。通过对三个经典测试函数优化问题的数值仿真并与其它方法进行比较,结果表明了算法的有效性和实用性。     

Multi-objective fuzzy particle swarm optimization based on elite archiving and its convergence

A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.