A HYBRID METHOD FOR SOLVING VARIATIONAL INEQUALITY PROBLEMS

§ 1　IntroductionThe problem of finding a point x* ∈S such that〈F(x* ) ,x -x* 〉≥ 0 for all x∈ S,(VIP)where S is a nonempty closed convex subset of Rn,F is a mapping from Rninto itself,and〈.,.〉denotes the inner productin Rn,is called the variational inequality problem and hasbeen widely used to study various equilibrium models arising in economic,operations re-search,transportation and regional sciences[1 ,2 ] .Many iterative methods for (VIP) havebeen developed,for example,project…     

Dynasearch for the earliness-tardiness scheduling problem with release dates and setup constraints

A large dynasearch neighborhood is introduced for the one-machine scheduling problem with sequence-dependent setup times and costs and earliness-tardiness penalties. Finding the best schedule in this neighborhood is NP-complete in the ordinary sense but can be done in pseudo-polynomial time. We also present experimental results.     

略论两种"Beilstein大全"查阅法

本文介绍了两种查阅“Beilstein大全”(拜尔斯坦有机化学大全)的实用方法，即通过化学品供货商的供货目录或相关的理化手册、产品手册检索和用系统图解检索，并对这些简要实用的方法进行了分析、对比和评价。     

Hybrid evolutionary algorithm for solving general variational inequality problems

This paper considers the problem of finding as many as possible, hopefully all, solutions of the general (i.e., not necessarily monotone) variational inequality problem (VIP). Based on global optimization reformulation of VIP, we propose a hybrid evolutionary algorithm that incorporates local search in promising regions. In order to prevent searching process from returning to the already detected global or local solutions, we employ the tunneling and hump-tunneling function techniques. The proposed algorithm is tested on a set of test problems in the MCPLIB library and numerical results indicate that it works well in practice.     

一种改进的禁忌搜索算法及其在选址问题中的应用

本文研究了选址问题中无容量限制的p-中值问题,在Rolland等人提出的有效禁忌搜索算法基础上,提出了一种以目标函数变化量作为评价函数的改进禁忌搜索算法,并进行了理论分析,然后将其与有效禁忌搜索算法作了性能比较.通过比较三个公共测试数据集的计算结果,验证了本文提出的禁忌搜索算法的可行性和有效性.     

A Petri Net based algorithm for minimizing total tardiness in flexible manufacturing systems

Petri Nets have been extensively used for modeling and simulating of the dynamics of flexible manufacturing systems. Petri Nets can capture features such as parallel machines, alternative routings, batch sizes, multiplicity of resources, to name but a few. However, Petri Nets have not been very popular for scheduling in manufacturing due to the Petri Net “state explosion” combined with the NP-hard nature of many of such problems. A promising approach for scheduling consists of generating only portions of the Petri Net state space with heuristic search methods. Thus far, most of this scheduling work with Petri Nets has been oriented to minimize makespan. The problem of minimizing total tardiness and other due date-related criteria has received little attention. In this paper, we extend the Beam A^* Search algorithm presented in a previous work with capability to handle the total tardiness criterion. Computational tests were conducted on Petri Net models of both flexible job shop and flexible manufacturing systems. The results suggest that the Petri Net approach is also valid to minimize due date related criteria in flexible systems.     

基于非单调线搜索非拟牛顿法的全局收敛性

本文就非拟牛顿法在无约束最优化问题上，对采用非单调线搜索的情况下是否具有全局收敛性进行了研究，在目标函数满足一致凸的条件下，证明了非拟牛顿族是全局收敛的．     

K-Harmonic means data clustering with tabu-search method

Clustering is a popular data analysis and data mining technique. Since clustering problem have NP-complete nature, the larger the size of the problem, the harder to find the optimal solution and furthermore, the longer to reach a reasonable results. A popular technique for clustering is based on K-means such that the data is partitioned into K clusters. In this method, the number of clusters is predefined and the technique is highly dependent on the initial identification of elements that represent the clusters well. A large area of research in clustering has focused on improving the clustering process such that the clusters are not dependent on the initial identification of cluster representation. Another problem about clustering is local minimum problem. Although studies like K-Harmonic means clustering solves the initialization problem trapping to the local minima is still a problem of clustering. In this paper we develop a new algorithm for solving this problem based on a tabu search technique—Tabu K-Harmonic means (TabuKHM). The experiment results on the Iris and the other well known data, illustrate the robustness of the TabuKHM clustering algorithm.     

There are 1239 Steiner Triple Systems STS(31) of 2-rank 27

A computer search over the words of weight 3 in the code of blocks of a classical Steiner triple system (STS) on 31 points is carried out to classify all STS(31) whose incidence matrix has 2-rank equal to 27, one more than the possible minimum of 26. There is a total of 1239 nonisomorphic STS(31) of 2-rank 27.     

Target aiming Pareto search and its application to the vehicle routing problem with route balancing

In this paper, we present a solution method for a bi-objective vehicle routing problem, called the vehicle routing problem with route balancing (VRPRB), in which the total length and balance of the route lengths are the objectives under consideration. The method, called Target Aiming Pareto Search, is defined to hybridize a multi-objective genetic algorithm for the VRPRB using local searches. The method is based on repeated local searches with their own appropriate goals. We also propose an implementation of the Target Aiming Pareto Search using tabu searches, which are efficient meta-heuristics for the vehicle routing problem. Assessments with standard metrics on classical benchmarks demonstrate the importance of hybridization as well as the efficiency of the Target Aiming Pareto Search.