一类艾滋病传播的数学模型的定态非负解

利用分歧理论讨论带扩散问题艾滋病传播数学模型定态非负解及全局性质．     

Cubic and Quartic Convergence for First-Order Periodic Boundary-Value Problems

In this paper, the results of Lakshmikantham et al. (Ref. 1) for first-order periodic boundary-value problems are extended, by using the extended method of quaislinearization and rapid convergence for initial-value problems of Mohapatra et al. (Ref. 2). Also, it is shown that monotone sequences converge cubically to the unique solution when the forcing function in the differential equation is 2–hyperconvex and converge quartically when the forcing function is 3–hyperconvex. Several other generalizations of the problem are also presented.     

非线性约束优化问题的一个修正 Lagrangian 算法

基于一个含有控制参数的修正Lagrangian函数,该文建立了一个求解非线性约束优化问题的修正Lagrangian算法.在一些适当的条件下,证明了控制参数存在一个阀值,当控制参数小于这一阀值时,由这一算法产生的序列解局部收敛于问题的Kuhn-Tucker点,并且建立了解的误差上界.最后给出一些约束优化问题的数值结果.     

某类实解析与复解析分歧问题的R-有限决定及K-有限决定问题的注记

该文给出了某类实解析与复解析分歧问题是不能R-有限决定的．并利用上述结果证明了一类分岐问题是不能K-有限决定的．同时给出了一个K-有限决定但不能R-有限决定的个例子,它说明在分岐问题中R-有限决定与K-有限决定不是互为充要的条件．     

Statistical physics, optimization and source coding

The combinatorial problem of satisfying a given set of constraints that depend on N discrete variables is a fundamental one in optimization and coding theory. Even for instances of randomly generated problems, the question “does there exist an assignment to the variables that satisfies all constraints?” may become extraordinarily difficult to solve in some range of parameters where a glass phase sets in. We shall provide a brief review of the recent advances in the statistical mechanics approach to these satisfiability problems and show how the analytic results have helped to design a new class of message-passing algorithms — the survey propagation (SP) algorithms — that can efficiently solve some combinatorial problems considered intractable. As an application, we discuss how the packing properties of clusters of solutions in randomly generated satisfiability problems can be exploited in the design of simple lossy data compression algorithms.     

Interior projection-like methods for monotone variational inequalities

We propose new interior projection type methods for solving monotone variational inequalities. The methods can be viewed as a natural extension of the extragradient and hyperplane projection algorithms, and are based on using non Euclidean projection-like maps. We prove global convergence results and establish rate of convergence estimates. The projection-like maps are given by analytical formulas for standard constraints such as box, simplex, and conic type constraints, and generate interior trajectories. We then demonstrate that within an appropriate primal-dual variational inequality framework, the proposed algorithms can be applied to general convex constraints resulting in methods which at each iteration entail only explicit formulas and do not require the solution of any convex optimization problem. As a consequence, the algorithms are easy to implement, with low computational cost, and naturally lead to decomposition schemes for problems with a separable structure. This is illustrated through examples for convex programming, convex-concave saddle point problems and semidefinite programming.The work of this author was partially supported by the United States–Israel Binational Science Foundation, BSF Grant No. 2002-2010.     

The shape of an axisymmetric bubble in uniform motion

We consider in a frame fixed to a bubble translating with steady speedU, the inviscid, axisymmetric, irrotational motion of the liquid past it. If all speeds are normalized byU and lengths by {ie437-1}, whereT is the surface tension of the liquid-bubble interface, it can be shown that the unknown bubble shape and field depend on a single parameter {ie437-2} alone, where the pressures are the ones in the bubble and far away respectively. WhenΓ is very large the bubble is almost spherical in shape while for Γ<- Γ^* ≈ -0.315, bubbles whose exteriors are simply connected do not exist. We solve the non-linear, free boundary problem for the whole range Γ^* < Γ < ∞ by the use of an analytical representation for the bubble shape, a surface singularity method to compute potential flows and a generalized Newton’s method to continue inΓ. Apart from providing explicit representations for bubble shapes and detailed numerical values for the bubble parameters, we show that the classical linearized solution for largeΓ is a very good approximation, surprisingly, to as low values of Γ as 2. We also show that Miksiset al [1] is inaccurate over the whole range and in serious error for large and smallΓ. These have been corrected.     

Some Remarks On Vector Optimization Problems

We prove the existence of a weak minimum for vector optimization problems by means of a vector variational-like inequality and preinvex mappings.