一种基于约束的指针程序路径选择方法

动态符号执行是对程序进行安全性分析的重要技术.在动态符号执行过程中,存在着符号地址,系统调用,路径选择等问题.针对符号地址导致的别名分析问题,本文提出了一种基于约束的指针分析方法,对程序进行过程内的指向分析,并对指针分析过程引入约束条件,产生可以进行路径选择的测试用例,以提高指针分析的精度.在国内首款某型号商用编译器的开发过程中实现了该方法,实验结果表明,该方法可以准确地分析C语言测试用例,缩短用例测试的时间.     

Constraints and Soliton Solutions for KdV Hierarchy and AKNS Hierarchy

It is well-known that the finite-gap solutions of the KdV equationcan be generated by its recursion operator.We generalize the result to a special form of Lax pair,from which a method to constrain the integrable system to alower-dimensional or fewer variable integrable system is proposed.A direct result is that the n-soliton solutions of the KdV hierarchy can be completely depictedby a series of ordinary differential equations (ODEs), which may be gotten by a simple but unfamiliar Lax pair. Furthermore the AKNS hierarchy is constrained to a series of univariate integrable hierarchies. The key is a special form of Lax pair for the AKNS hierarchy. It is proved that under the constraints all equations of the AKNS hierarchy are linearizable.     

约束含参分岔问题的分类

约束边界与分岔参数有关的约束分岔问题,称为约束含参分岔问题．通过引入适当的变换,将约束含参分岔问题转化为新变量的非约束分岔问题,推导出了约束含参分岔问题转迁集的一般形式,结果表明只有约束分岔集受约束含参的影响,其它转迁集与不含参约束分岔的转迁集相同．以含参约束树枝分岔为例分析了此类问题的分岔分类,讨论了约束含参对分岔分类的影响．     

基于柔性契约的政府应急物资采购模型研究

面对突发事件导致的巨大物资需求,实物储备往往体现出应对能力不足。而对于生产时间较短的重要应急物资,生产能力储备是缓解这一压力的有效途径。对此,本研究构建了一个物资企业双储备形式下的应急物资采购模型,分析研究了在物资企业可以选择生产形式(常规生产和加急生产)的情况下,政府的最优支付决策和物资企业的双储备决策。推导分析结果显示,物资企业的生产能力约束和政府的支付水平对政企合作形式起到决定性作用。本研究进一步通过数值分析验证模型的有效性和契约合作的优势,并讨论了若干重要外生参数对政企最优决策的影响。     

浅海时变声速环境下的自适应匹配场定位算法实现*

针对浅海环境下声速剖面失配引起的匹配场处理器失配问题,提出了一种自适应匹配场定位算法在声速剖面时变环境下的实现方式。将先验声速剖面集简化为经验正交函数表示,结合蒙特卡洛方法与环境扰动约束算法对当下时刻的目标声源进行匹配场定位。本文以某次试验获取的连续20小时的声速剖面数据为研究对象,通过仿真试验对该算法进行验证,结果表明：在先验声速剖面集的半小时之后,利用自适应算法的距离和深度定位成功率较常规匹配场算法有较大提升,其中,深度正确定位概率相对较低。     

机器带不可用时间限制的简单线性恶化供应链排序问题

研究的单机供应链排序问题中, 机器有一个不可用时间限制, 工件的加工时间与恶化率及其开工时间有关, 且工件的加工不可恢复. 一个或多个完工工件可组成一个发送批由车辆发送给客户, 且在机器不可用时间限制之前完工的工件必须在限制开始之时或之前完成发送. 问题的目标是最小化总发送时间与总发送费用之和. 证明问题是NP-难的, 提出了伪多项式时间的动态规划算法. 进一步, 在确定问题目标函数值的上界及下界之后, 设计了一个完全多项式时间近似方案(FPTAS).     

树形多体系统动力学约束力算法

多体系统高效动力学算法一直是多体系统动力学的重要研究方向. 近年来,众多高效算法虽然在提高解算效率方面取得了一定研究成果,但大多无法直接给出多体系统的显式动力学方程或解算系统约束力. 基于以上问题,研究了适用于任意树形多体系统动力学解算的约束力算法(constraint force algorithm, CFA) 及其串行化应用. 约束力算法可在解算多体系统动力学的过程中对系统约束力进行求解,该算法串行化后计算量仅与自由度成线性关系. 通过分析树形多体系统中任意节点处的动力学、运动学递推关系并讨论系统方程的组集方法,将仅适用于链状系统的算法推广至任意树形系统,并给出了其串行化应用方法以提高算法效率. 在数值仿真中,将所提算法与递推算法进行对比,验证了所提出的约束力算法的准确性;此外,通过对比4 种不同算法在相同工作环境下解算同一模型时的处理器运行时间,证实了串行化约束力算法的高效性.      

Projected Runge-Kutta methods for constrained Hamiltonian systems

Projected Runge-Kutta (R-K) methods for constrained Hamiltonian systems are proposed. Dynamic equations of the systems, which are index-3 differential-algebraic equations (DAEs) in the Heisenberg form, are established under the framework of Lagrangian multipliers. R-K methods combined with the technique of projections are then used to solve the DAEs. The basic idea of projections is to eliminate the constraint violations at the position, velocity, and acceleration levels, and to preserve the total energy of constrained Hamiltonian systems by correcting variables of the position, velocity, acceleration, and energy. Numerical results confirm the validity and show the high precision of the proposed method in preserving three levels of constraints and total energy compared with results reported in the literature.     

Plate/shell topological optimization subjected to linear buckling constraints by adopting composite exponential filtering function

In this paper, a model of topology optimization with linear buckling constraints is established based on an independent and continuous mapping method to minimize the plate/shell structure weight. A composite exponential function (CEF) is selected as filtering functions for element weight, the element stiffness matrix and the element geomet-ric stiffness matrix, which recognize the design variables, and to implement the changing process of design variables from“discrete”to“continuous”and back to“discrete”. The buck-ling constraints are approximated as explicit formulations based on the Taylor expansion and the filtering function. The optimization model is transformed to dual programming and solved by the dual sequence quadratic programming algo-rithm. Finally, three numerical examples with power function and CEF as filter function are analyzed and discussed to demonstrate the feasibility and efficiency of the proposed method.