线性分式多乘积规划问题的完全多项式时间近似算法

本文针对线性分式多乘积规划问题,通过Charnes-Cooper转化将原问题转化为一个等价问题,借助此等价问题提出一个获得原问题全局近似最优解的算法,最终证明了算法的收敛性,且提供了算法运算时间的理论分析.     

An objective space cut and bound algorithm for convex multiplicative programmes

Multiplicative programming problems are global optimisation problems known to be NP-hard. In this paper we propose an objective space cut and bound algorithm for approximately solving convex multiplicative programming problems. This method is based on an objective space approximation algorithm for convex multi-objective programming problems. We show that this multi-objective optimisation algorithm can be changed into a cut and bound algorithm to solve convex multiplicative programming problems. We use an illustrative example to demonstrate the working of the algorithm. Computational experiments illustrate the superior performance of our algorithm compared to other methods from the literature.     

Multiobjective linear programming with context-dependent preferences

Multiobjective linear programming algorithms are typically based on value maximization. However, there is a growing body of experimental evidence showing that decision maker behavior is inconsistent with value maximization. Tversky and Simonson provide an alternative model for problems with a discrete set of choices. Their model, called the componential context model, has been shown to capture observed decision maker behavior. In this paper, an interactive multiobjective linear programming algorithm is developed which follows the rationale of Tversky and Simonson. The algorithm is illustrated with an example solved using standard linear programming software. Finally, an interactive decision support system based on this algorithm is developed to field test the usefulness of the algorithm. Results show that this algorithm compares favorably with an established algorithm in the field.     

一类多乘积规划的加速算法

针对一类多乘积规划问题(MP),给出一个加速算法.首先导出一个与(MP)等价的逆凸问题(RCP),然后构造问题(RCP)的线性松弛化问题.算法的主要特点是提出了两个加速技巧,这些技巧可以用于改善算法的收敛速度.数值算例表明算法是可行的.     

On the computation of an element of Clarke generalized Jacobian for a vector-valued max function

In this paper, we present an algorithm for calculating an element of Clarke generalized Jacobian for a vector-valued max-type function. The algorithm reduces the computational cost of an existing algorithm.     

An algorithm for local continuous optimization of traffic signals

In this paper, an algorithm for sensitivity analysis for equilibrium traffic network flows with link interferences is proposed. Based on this sensitivity analysis algorithm, a general algorithm is provided for solving the optimal design and management problems for traffic networks. In particular, this algorithm is applied to the optimal traffic signal setting problem. A numerical example is given to demonstrate the effectiveness of our algorithm.     

An Arnoldi-Extrapolation algorithm for computing PageRank

The Arnoldi-type algorithm proposed by Golub and Greif [G. Golub, C. Greif, An Arnoldi-type algorithm for computing PageRank, BIT 46 (2006) 759-771] is a restarted Krylov subspace method for computing PageRank. However, this algorithm may not be efficient when the damping factor is high and the dimension of the search subspace is small. In this paper, we first develop an extrapolation method based on Ritz values. We then consider how to periodically knit this extrapolation method together with the Arnoldi-type algorithm. The resulting algorithm is the Arnoldi-Extrapolation algorithm. The convergence of the new algorithm is analyzed. Numerical experiments demonstrate the numerical behavior of this algorithm.     

New Algorithm for Computing LQ Suboptimal Output Feedback Gains of Decentralized Control Systems

In this paper, the problem of computing the suboptimal output feedback gains of decentralized control systems is investigated. First, the problem is formulated. Then, the gradient matrices based on the index function are derived and a new algorithm is established based on some nice properties. This algorithm shows that a suboptimal gain can be computed by solving several ordinary differential equations (ODEs). In order to find an initial condition for the ODEs, an algorithm for finding a stabilizing output feedback gain is exploited, and the convergence of this algorithm is discussed. Finally, an example is given to illustrate the proposed algorithm.     

An algorithm for the capacitated vehicle routing problem with route balancing

In this paper, we present a multi-objective evolutionary algorithm for the capacitated vehicle routing problem with route balancing. The algorithm is based on a formerly developed multi-objective algorithm using an explicit collective memory method, namely the extended virtual loser (EVL). We adapted and improved the algorithm and the EVL method for this problem. We achieved good results with this simple technique. In case of this problem the quality of the results of the algorithm is similar to that of other evolutionary algorithms.     

一种修正的求总极值的积分—水平集方法的实现算法收敛性

1978年,郑权等提出了一个积分型求总极值的概念性算法及Monte-Carlo随机投点的实现算法,给出了概念性算法的总极值存在的充分必要条件,但是其实现算法收敛性仍未解决,1986年,张连生等给出离散均值－水平集的实现算法,并证明了它的收敛性。本文给出修正的积分－水平集方法,用一致分布搂九值积分逼近水平集构造实现算法,并证明了算法的收敛性。