一种求解对称锥互补问题的算法

提出了一种求解对称锥互补问题的信赖域算法.基于光滑函数,将对称锥互补问题转化为无约束优化问题,构造了信赖域子问题,利用结合非单调策略的信赖域算法进行求解,并证明了该算法具有全局收敛性.仿真实验结果表明,算法对求解对称锥互补问题是有效的.     

基于二阶锥规划的自适应均衡算法

提出一种改进的均衡器算法。该方法基于最小均方误差（minimum mean square error, MMSE）准则,使均衡器的输出与训练码的均方误差最小,并且将信道均衡的最小均方误差目标函数转化为二阶锥形式,利用内点法求最优解。与传统基于最小均方误差（least mean squares, LMS）和递归最小二乘（recursive least squares, RLS）自适应算法的均衡器相比,由于不需要迭代收敛过程,不存在收敛速度与精度的矛盾,克服了基于LMS和RLS的自适应均衡器参数设置的困难,而且利用更短的训练序列长度即可获得相同的均衡效果,对于改善通信效率具有参考价值。     

基于代数变换求解P*(κ)阵线性互补问题的新算法

基于代数变换和不可行内点方法的思想,首次对P*(κ)阵线性互补问题提出了一种宽邻域不可行内点算法,并在较弱的条件下,证明了算法的全局Q—线性收敛性和多项式复杂性。该算法可看作关于线性规划不可行内点算法的推广,也是关于单调线性互补问题不可行内点算法的推广。     

基于代数变换求解P*(к)阵线性互补问题的新算法

基于代数变换和不可行内点方法的思想,首次对P*(к)阵线性互补问题提出了一种宽邻域不可行内点算法,并在较弱的条件下,证明了算法的全局Q-线性收敛性和多项式复杂性.该算法可看作关于线性规划不可行内点算法的推广,也是关于单调线性互补问题不可行内点算法的推广.     

基于二阶锥规划的峰值旁瓣抑制滤波器设计

针对相位编码信号的高旁瓣问题,提出一种基于二阶锥规化的峰值旁瓣抑制滤波器设计方法。将最大增益处理损失约束下的最小峰值旁瓣滤波器设计转化为二阶锥规化问题,采用内点法进行高效求解。与已有方法相比,所提方法可以兼顾峰值旁瓣、处理增益损失和滤波器长度三方面的指标,具有设计灵活、精度高和收敛性好的优点。最后仿真和实测数据结果验证了方法的有效性。     

一种求解混合整数非线性规划的新算法

针对混合整数非线性规划求解难的问题,本文给出了一种新的求解策略--混合序列差异演化算法,该算法采取混合编码的形式以便处理连续变量、整数变量以及混合整数变量的优化问题.最后通过数例检验算法的优越性,仿真结果表明该算法求解效率高、收敛速度快、全局搜索能力强.     

一种有效的进化规划算法

提出一种新的进化规划算法,该方法不仅能够加快普通进化规划算法的收敛速度,而且能够有效地保证种群的多样性,并用该方法求解具有多个极值点的函数优化问题,计算机仿真实验结果表明该方法是非常有效的。     

求解非线性互补问题的混合光滑型算法

光滑型算法已经成功地用来求解各种优化问题. 基于一类新的光滑函数族, 提出了一个带有混合线搜 索的光滑型算法求解非线性互补问题. 在适当的条件下, 证明了算法是适定的, 且保持全局 收敛性和局部超线性收敛性. 最后对提出的算法进行了数值计算. 数值结果显示出该算法的有效性.     

一种求解多目标规划的新方法

以多目标规划理论和数据拟合法为基础,把两者有机结合起来,提出了一种求解多目标规划的新方法,并给出了详细的算法过程.该方法的特点是对所研究的多目标规划问题,无须决策者提供关于所研究问题的全部信息,却又兼顾了决策者的偏好,还简化了优化准则,实现了决策者与系统的信息交流及对规划过程的参与,具有一定的灵活性和一般性.     

Exponential distribution-based genetic algorithm for solving mixed-integer bilevel programming problems

Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s functions are convex if the follower＇s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader＇s variable x, it is proved that the optimal solution y of the follower＇s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower＇s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.     

Improved genetic algorithm for nonlinear programming problems

An improved genetic algorithm(IGA) based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals’ feature vector.Additionally,a local search(LS) process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.     

多用户双向AF MIMO中继系统的联合预编码算法

近年,双向放大转发(amplify-and-forward, AF)多输入多输出(multiple input multiple output, MIMO)中继系统中的预编码设计吸引了越来越多研究学者的兴趣。然而,在实际MIMO中继通信系统中,针对双向传输下的系统,对多用户模型进行的研究较少。由此,针对多用户双向AF MIMO中继系统模型,提出了一种联合预编码算法。采用在所有节点功率限制下,以最小和均方误差(minimun sum mean square error, MSMSE)设计准则去求解联合信源、中继和信宿端多用户的非凸优化问题,将最初的非凸优化问题转化成多个子优化问题,并利用半正定规划设计、平方约束二次规划设计以及二阶锥规划设计求解子优化问题。之后通过交替迭代方法进一步求解每个子凸优化问题局部优化值,达到优化所有节点矩阵变量的目的。所提算法较现有的算法,不仅在优化问题方面考虑更全面、更实用,而且实验仿真结果验证,提出的算法在系统和均方误差(sum mean-square-error, SMSE)性能、和速率以及误码率(bit-error rate, BER)上有均有改善。     

A penalty function method for solving ill-posed bilevel programming problem via weighted summation

For ill-posed bilevel programming problem, the optimistic solution is always the best decision for the upper level but it is not always the best choice for both levels if the authors consider the model＇s satisfactory degree in application. To acquire a more satisfying solution than the optimistic one to realize the two levels＇ most profits, this paper considers both levels＇ satisfactory degree and constructs a minimization problem of the two objective functions by weighted summation. Then, using the duality gap of the lower level as the penalty function, the authors transfer these two levels problem to a single one and propose a corresponding algorithm. Finally, the authors give an example to show a more satisfying solution than the optimistic solution can be achieved by this algorithm.     

Method for solving fully fuzzy linear programming problems using deviation degree measure

A new fully fuzzy linear programming （FFLP） problem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crisp 6-parametric linear programming （LP） problem. Giving the value of deviation degree in each constraint, the 6-fuzzy optimal solution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict： to improve the values of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to illustrate the proposed method.     

改进差分进化算法求解武器目标分配问题

针对武器目标分配问题求解收敛速度慢、搜索效率低、寻优精度差的问题,提出一种基于改进差分进化算法的武器目标分配方法.首先,建立多约束条件下武器目标分配优化模型,将动态武器目标分配问题离散为静态武器目标分配问题处理.其次,采用随机邻域变异策略平衡差分进化算法全局探索和局部开发能力,采用基于历史存档的自适应参数整定方法,根据...     

SRV constraint based FIB design for wideband linear array

Frequency-invariant beamformer (FIB) design is a key issue in wideband array signal processing. To use commonly wideband linear array with tapped delay line (TDL) structure and complex weights, the FIB design is provided according to the rule of minimizing the sidelobe level of the beampattern at the reference frequency while keeping the distortionless response constraint in the mainlobe direction at the reference frequency, the norm constraint of the weight vector and the amplitude constraint of the averaged spatial response variation (SRV). This kind of beamformer design problem can be solved with the interior-point method after being converted to the form of standard second order cone programming (SOCP). The computer simulations are presented which illustrate the effectiveness of our FIB design method for the wideband linear array with TDL structure and complex weights.     

求解非线性双层规划问题的混合变邻域粒子群算法

针对非线性双层规划难以获得全局最优的问题,汲取粒子群算法的快速搜索能力及变邻域搜索算法的全局搜索优势,提出了求解非线性双层规划问题的混合变邻域粒子群算法.首先利用Kuhn-Tucker条件,将非线性双层规划转化为一个单层规划问题,然后由粒子群算法得到一个较优的群体,通过审敛因子判断陷入局部最优的粒子,并进一步利用变邻域搜索算法的全局搜索能力对陷入局部最优的粒子进行优化,从而得到全局最优.测试函数的仿真实验对比分析证明了该算法的有效性.