初始点任意的一个非线性优化的广义梯度投影法

广义投影算法的优点是避免转轴运算。它成功地给出了线性约束问题、初始点任意的只带非线性不等式约束问题，以及利用辅助规划来处理带等式与不等式约束问题的算法．后者完满地解决了投影算法对于非线性等式约束问题的处理，但要求满足不等式约束的初始点．本文据此利用广义投影与罚函数技巧给出了一个初始点任意的等式与不等式约束问题的算法，省去了求初始解的计算，并保持了上述方法的优点，证明了算法的全局收敛性     

级联掺磷光纤喇曼激光器的解析优化

讨论了二级级联喇曼光纤激光器的解析解和优化设计.通过引入几何平均功率、增益因子和归一化光纤有效长度,将描述泵浦光和斯托克斯光沿喇曼增益光纤分布的微分方程组简化成代数方程组,在对泵浦光采用线性传播近似后,获得了二级级联喇曼激光器的解析解.所获得的解析解同数值模拟结果吻合得很好.利用该解析解可方便和快速地讨论级联喇曼激光器的优化设计,计算不同泵浦功率下的最佳光纤长度、输出光纤光栅反射率和转换效率.泵谱功率越大,最佳光纤长度越短,最佳输出光纤光栅反射率越小.     

Mathematical Analysis of caching policies and cooperation in YouTube-like services

Currently, most video on-demand services offered over the Internet do not exploit the idle resources available from end-users. We discuss the benefits of user-assistance in video on-demand systems, where users are both clients and servers, helping with the task of video distribution. The mathematical machinery for the systematic analysis of video on-demand services is not mature yet. In this paper we develop a deterministic fluid model to determine the expected evolution of user-assisted on-demand video streaming services. We theoretically prove that cooperative systems always outperform non-cooperative solutions. A combinatorial optimization problem is proposed, where the goal is to distribute a set of video items into repositories trying to offer the minimum waiting times to end-users. This combinatorial problem is proved to be in the class of NP-Complete computational problem, and is heuristically solved with a GRASP methodology. Predictions inspired in YouTube scenarios suggest the introduction of cooperation is both robust and extremely attractive from an economical viewpoint as well.     

A Branch-and-price Algorithm for the Multi-Vehicle Covering Tour Problem

In this paper, we propose a Branch-and-price (BP) algorithm and a Column Generation Heuristic (CGH) for the Multi-Vehicle Covering Tour Problem (m-CTP). Specific dominance and extension pruning rules are introduced to accelerate the resolution of the pricing problems. To the best of our knowledge, this is the first work dedicated to the exact resolution of m-CTP. The algorithm managed to solve about 30% of the instances in our test bed, within a 4 hour CPU time limit. Our preliminary computational experiments suggest that both the lower bounds provided by the formulation behind BP and the CGH upper bounds are of good quality.     

Position of starting spot in TLC: Influence on average plate height

Summary The influence of the distance between the solvent entry and the starting zone positions, Z₀, on the average plate height was studied. This factor was found to be of major importance and could be optimized. The Guiochon and Siouffi model greatly underestimates the plate height for low values of Z₀.     

Detecting embedded pure network structures in LP problems

Recently, linear programming problems with special structures have assumed growing importance in mathematical programming. It is well known that exploiting network structures within linear programs can lead to considerable improvement of the computational solution of large-scale linear programming problems. A linear program is said to contain an embedded network structure provided that some subset of its constraints can be interpreted as specifying conservation of flow. If a column of the constraint matrix has at most two non-zeros, then it leads to embedded generalized network structure and if these non-zeros are unit elements and of opposite signs, then it leads to embedded pure network structure. In this paper, we are concerned with algorithms for detecting embedded pure network structures within linear programs. The network extraction methods are presented in two groups. The first group covers deletion and addition based algorithms and the second group covers GUB based algorithms. We have extended the GUB based algorithm appearing in the second group by introducing Markowitz merit count approach for exploiting matrix non zeros. A set of well known test problems has been used to carry out computational experiments which show that our extensions to the GUB based algorithms give better results than the algorithms reported earlier.     

Computational aspects of two-segment separable programming

Recursive separable programming algorithms based on local, two-segment approximations are described for the solution of separable convex programs. Details are also given for the computation of lower bounds on the optimal value by both a primal and a dual approach, and these approaches are compared. Computational comparisons of the methods are provided for a variety of test problems, including a water supply application (with more than 600 constraints and more than 900 variables) and an econometric modelling problem (with more than 200 variables). Research supported by National Science Foundation Grants MCS74-20584 A02 and MCS-7901066.     

Optimal numerical method for simulating dynamic flow of gas in pipelines

Finite difference methods for solving the linear model describing unsteady state flow in pipelines are considered in the present paper. These methods are compared with each other in order to determine the best one, which meets the criteria of accuracy and relatively small computation time.     

Elimination of bounds in optimization problems by transforming variables

The problem of minimizing a nonlinear objective function ofn variables, with continuous first and second partial derivatives, subject to nonnegativity constraints or upper and lower bounds on the variables is studied. The advisability of solving such a constrained optimization problem by making a suitable transformation of its variables in order to change the problem into one of unconstrained minimization is considered. A set of conditions which guarantees that every local minimum of the new unconstrained problem also satisfies the first-order necessary (Kuhn—Tucker) conditions for a local minimum of the original constrained problem is developed. It is shown that there are certain conditions under which the transformed objective function will maintain the convexity of the original objective function in a neighborhood of the solution. A modification of the method of transformations which moves away from extraneous stationary points is introduced and conditions under which the method generates a sequence of points which converges to the solution at a superlinear rate are given.     

A Point Balance Algorithm for the Spherical Code Problem

The Spherical Code (SC) problem has many important applications in such fields as physics, molecular biology, signal transmission, chemistry, engineering and mathematics. This paper presents a bilevel optimization formulation of the SC problem. Based on this formulation, the concept of balanced spherical code is introduced and a new approach, the Point Balance Algorithm (PBA), is presented to search for a 1-balanced spherical code. Since an optimal solution of the SC problem (an extremal spherical code) must be a 1-balanced spherical code, PBA can be applied easily to search for an extremal spherical code. In addition, given a certain criterion, PBA can generate efficiently an approximate optimal spherical code on a sphere in the n-dimensional space ⁿ. Some implementation issues of PBA are discussed and putative global optimal solutions of the Fekete problem in 3, 4 and 5-dimensional space are also reported. Finally, an open question about the geometry of Fekete points on the unit sphere in the 3-dimensional space is posed.