基于控制工序性质的LOB截止日期问题分析与算法

截止日期问题是重复性项目调度中研究最为广泛的问题之一,其旨在满足项目截止日期前提下求得一个工作队雇佣总量最小的调度方案。由于重复性项目往往为大型工程建设项目,一个准确的最优进度计划对于节约项目的资源和成本具有重要意义。在平衡线法(LOB)框架下,本文从控制工序的性质出发,研究并分析了控制工序工作队分配与项目总工期之间的关联,给出了截止日期问题的一些特殊性质。基于这些性质,一方面能够帮助项目管理人员判断一个调度方案是否可行且经济,另一方面能够得到一些有效的剪枝策略,从而设计出具有针对性的分支限界算法。最后,通过案例计算和仿真实验验证了本文提出的算法在计算效果和计算效率上的有效性。     

免疫算法在车辆调度问题中的应用

免疫算法是模仿生物体高度进化、复杂的免疫系统仿生的一种智能化启发式算法。本文根据车辆调度问题的具体情况，应用免疫算法解决车辆调度中路线安排问题，并提出了一种基于分组匹配的亲和力的计算方法。实验结果表明，免疫算法能有效地应用于车辆调度中路线安排问题。     

一个最优指派问题及其算法

设有n项工作.第j(1≤j≤n)项工作需要b_j个工人共同完成.现有m=sum from j=1 to ? b_j个工人,每人做任一工作的产值为已知.如何安排使总产值最高?这一问题是指派问题和[1]中问题的推广。我们给出了这个问题的算法,本文的算法比[1]中算法简便易学。     

一类流水作业的安排问题

本文研究一类流水作业的安排问题.在收益大损失小的目标下,提出一些调整工艺流程的原则,并以服装加工为例进行说明.在流水作业的安排中,工序的划分、每道工序上的工作能力(包括劳动力、设备、工作条件等)、每台设备所能担负的工序以及加工的批量往往是可变的.安排的合理与否直接影响到产值和损失的大小,这类问题的目标显然应该是产值大损失小.为达到合理安排的效果,首先应按工序关系,排出工序流线图,也常称流水网络.我们     

坚持科学发展观 龙江珠协谱新篇——黑龙江省珠算协会2005年十件大事

一、1月30～31日，黑龙江省珠算协会在哈尔滨市召开全省市（地）珠协秘书长工作会议。省财政厅副厅长孙敏强出席会议并作重要讲话．会议对2004年全省珠协工作进行总结，并表彰在2004年工作中取得优异成绩的市地珠协；同时安排部署2005年全省珠协工作。     

双轮驱动治理财报舞弊

在中国正处于新兴加转型的经济格局下，如何剖析财务报表舞弊现象，并从制度层面安排治理策略，是亟待解决的现实问题。     

探讨线性代数的核心

本文从关于线性代数基本结构的各种不同看法出发，探讨线性代数在整个数学学习中的基本问题，并根据线性代数基本问题讨论线性代数的结构安排.     

求解空间Packing问题的实用近似快速算法

求解Packing问题在科学研究和生产实践中均有意义,例如航天火箭弹舱中诸仪器的几何布局工作,运输业中仓库与集装箱内的货物安排工作,就其实质而言主要地是求解Packing问题,由于问题具有NP难度,看来不可能存在精确、完整而又不是太慢的解法。目前在宇航与运输部门已开始探索有关工作的计算机辅助设计技术。求解空间Packing     

首份中国APA年度报导告

中国国家税务总局（“国税总局”）于2010年12月发布了《中国预约定价安排年度报告（2009）》（以下简称“预约定价安排报告”）。这一开创性的举动意味着,继美国、加拿大、澳大利亚、日本、韩国和意大利之后,中国也开始以发布年度报告的方式对预约定价安排工作的进展,对外进行全面详尽的介绍。 内容 预约定价安排报告由国税总局王力作序,并在正文之前对整篇报告做了一个简短的介绍说明。报告主体由4个章节组成,并附上了在预约定价安排申请及谈签过程中涉及的12份表证单书。整篇报告包括的主要内容如下：     

省珠协三届八次常务理事扩大会议总结

省珠协三届八次常务理事(扩大)会议，开了两天，现在就要结束了，出席这次会议的代表共45人，经过大家认真讨论，对需要解决的问题和今后的工作安排基本上达成了共识，可以说圆满地完成了本次会议的各项议程。     

Problem difficulty of real instances of convoy planning

Moving men and materials in large numbers and quantities is a long-standing military problem faced by all arms. An important part of this is the routing of convoys so that they reach their correct destinations in the shortest time. The optimization problem at the heart of this problem is referred to as the convoy movement problem. Previous work on the convoy movement problem has made the assumption that the problem is difficult in practice because of the NP-hardness of the problem in combination with the limited success of early approaches based on genetic algorithms. As a result subsequent work has focused on mathematical programming-based methods, principally Lagrangian relaxation. In this paper, we demonstrate that a straightforward reformulation of the problem renders the real-world like instances, used to benchmark previous approaches, amenable to solution by simple heuristics. The main lessons learnt from this work is that analysis of the problem in conjunction with simple algorithms can, in practice, yield surprisingly effective solutions.     

Using fuzzy numbers in knapsack problems

This paper investigates knapsack problems in which all of the weight coefficients are fuzzy numbers. This work is based on the assumption that each weight coefficient is imprecise due to the use of decimal truncation or rough estimation of the coefficients by the decision-maker. To deal with this kind of imprecise data, fuzzy sets provide a powerful tool to model and solve this problem. Our work intends to extend the original knapsack problem into a more generalized problem that would be useful in practical situations. As a result, our study shows that the fuzzy knapsack problem is an extension of the crisp knapsack problem, and that the crisp knapsack problem is a special case of the fuzzy knapsack problem.     

A note on a Cauchy problem for the Laplace equation: Regularization and error estimates

In this paper, a Cauchy problem for the Laplace equation is investigated. Based on the fundamental solution to the elliptic equation, we propose to solve this problem by the truncation method, which generates well-posed problem. Then the well posedness of the proposed regularizing problem and convergence property of the regularizing solution to the exact one are proved. Error estimates for this method are provided together with a selection rule for the regularization parameter. The numerical results show that our proposed numerical methods work effectively. This work extends to earlier results in Qian et al. (2008) [14] and Hao et al. (2009) [5].     

Polynomial Time Approximation Scheme for Two Parallel Machines Scheduling with a Common Due Date to Maximize Early Work

We study the scheduling problem with a common due date on two parallel identical machines and the total early work criterion. The problem is known to be NP-hard. We prove a few dominance properties of optimal solutions of this problem. Their proposal was inspired by the results of some auxiliary computational experiments. Test were performed with the dynamic programming algorithm and list algorithms. Then, we propose the polynomial time approximation scheme, based on structuring problem input. Moreover, we discuss the relationship between the early work criterion and the related late work criterion. We compare the computational complexity and approximability of scheduling problems with both mentioned objective functions.     

Some Fixed-Point Results for the Dynamic Assignment Problem

In previous work the authors consider the dynamic assignment problem, which involves solving sequences of assignment problems over time in the presence of uncertain information about the future. The algorithm proposed by the authors provides generally high-quality but non-optimal solutions. In this work, though, the authors prove that if the optimal solution to a dynamic assignment problem in one of two problem classes is unique, then the optimal solution is a fixed point under the algorithm.     

The regularizing properties of anisotropic radial basis functions

In the present work we consider the problem of interpolating scattered data using radial basis functions (RBF). In general, it is well known that this leads to a discrete linear inverse problem that needs to be regularized in order to provide a meaningful solution. The work focuses on a metric-regularization approach, based on a new class of RBF, called anisotropic RBF. The work provides theoretical justifications for the regularization approach and it considers a suitable proposal for the metric, supporting it by numerical examples.     

有限个渐近伪压缩映射近迫点序列的收敛性

研究了Banach空间中有限个渐近伪压缩映射近迫点序列的收敛性问题,此结果推广了以前的结论.     

The Development of Information Guided Evolution Algorithm for Global Optimization

Evolutionary algorithm (EA) has become popular in global optimization with applications widely used in many industrial areas. However, there exists probable premature convergence problem when rugged contour situation is encountered. As to the original genetic algorithm (GA), no matter single population or multi-population cases, the ways to prevent the problem of probable premature convergence are to implement various selection methods, penalty functions and mutation approaches. This work proposes a novel approach to perform very efficient mutation to prevent from premature convergence by introducing the concept of information theory. Information-guided mutation is implemented to several variables, which are selected based on the information entropy derived in this work. The areas of search are also determined on the basis of the information amount obtained from previous searches. Several benchmark problems are solved to show the superiority of this information-guided EA. An industrial scale problem is also presented in this work.     

A column generation approach for an employee scheduling problem with multiple shifts and work locations

This paper is concerned with the problem of assigning employees to a number of work centres taking into account employees' expressed preferences for specific shifts, off-days, and work centres. This particular problem is faced by the Kuwait National Petroleum Corporation that hires a firm to prepare schedules for assigning employees to about 86 stations distributed all over Kuwait. The number of variables in a mixed-integer programming model formulated for this problem is overwhelming, and hence, a direct solution to even the continuous relaxation of this model for relatively large-scale instances is inconceivable. However, we demonstrate that a column generation method, which exploits the special structures of the model, can readily solve the continuous relaxation of the model. Based on this column generation construct, we develop an effective heuristic to solve the problem. Computational results indicate that the proposed approach can facilitate the generation of good-quality schedules for even large-scale problem instances in a reasonable time.     

A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling

We develop a heuristic procedure for solving the discrete time/resource trade-off problem in the field of project scheduling. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero, which require one or more constrained renewable resources. Each activity has a specified work content and can be performed in different modes, i.e. with different durations and resource requirements, as long as the required work content is met. The objective is to schedule each activity in one of its modes in order to minimize the project makespan. We use a scatter search algorithm to tackle this problem, using path relinking methodology as a solution combination method. Computational results on randomly generated problem sets are compared with the best available results indicating the efficiency of the proposed algorithm.