基于蚂蚁算法的用户平衡分配方法研究

在介绍蚂蚁算法基础上给出了基于蚂蚁算法的用户平衡分配模型算法设计,并结合算例讨论了蚂蚁算法应用于用户平衡分配的可行性.最后进行了与F-W算法的比较分析,分析结果表明,蚂蚁算法求得的结果满足用户平衡分配的要求,同时表现出求解结果合理和寻优能力强的特点.     

公益事业中的角色分配

公益事业，已经成为推动社会发展不可或缺的一个因素，创建一个可持续发展的公益事业环境体系，并非只是一个有良知的社会组织或企业能够单独胜任的，在这个体系中，政府、国际组织，民间NGO、社会企业家、企业……各自扮演着不同角色.     

动画作品角色塑造的技巧探索

角色塑造是一部动画片创作的重中之重,其质量直接影响着影片的魅力和在产业链条上的盈利空间,而这个塑造过程则渗透在整个创作的各个环节,创作者不仅要做好到前期设定精准、丰富,也要在中后期利用各种元素不断深化角色,这样才能令角色更加深入人心。     

双运量约束下的OD分布与随机用户均衡交通分配组合模型

建立了在起点交通产生总量固定和在讫点交通吸引总量固定约束下的OD分布与随机用户均衡交通分配模型,并证明了该极值模型与随机用户均衡及OD分布要求的等价性,并设计了启发式算法来求解。     

浅谈用户自动化技术的研究和应用

用户自动化技术是智能电网建设的关键内容,是智能配电网建设的重要应用。文章分析了建设用户自动化技术的意义,阐述了用户自动化技术的研究现状,围绕用户自动化技术项目实践进行了总结与思考,并对用户自动化技术领域的未来进行了展望。     

基于用户分类的可聚类性IPv6地址分配

本文通过研究驻地网分配的IPv6可聚合全球单播地址,对其16位SLA ID和64位接口ID进行合理划分,提出一种基于用户分类的可聚类性IPv6地址分配方案.该方案较好的满足了IPv6路由要求,同时为IPv6网络的用户管理提供了便捷.     

基于多属性决策的城市水资源分配方案的选择

如何在各成员间进行使用权的合理分配是城市水资源管理亟需解决的关键问题.利用多属性决策方法,对城市水资源分配方案的选择进行了研究.研究过程中,提出了应将城市居民,三次产业的生产者,地方政府和相关领域专家纳入水资源分配的决策者集;同时,应在兼顾效率、环境和公平的基础上形成备选方案的属性集;并且,通过实例分析,说明了最优分配...     

交互分配法在辅助生产费用分配中的运用

交互分配法是企业在计算产品生产成本时,对辅助生产部门归集的费用的一种分配方法。采用交互分配法时,辅助生产部门归集的费用需要经过两次分配才能完成。第一次分配是将各辅助生产部门所归集的费用,按照它们所提供的产品或劳务的数量,分配给各受益的车间或部门,各辅助生产部门之间相互提供的产品或劳务也要接受分配;第二次分配是将各辅助生产部门交互分配后的实际费用,即交互分配前的费用加上第一次交互分配转入的费用,减去交互分配转出的费用,再按直接分配法或顺序分配法在各受益单位之间进行分配。按照第一次分配对象的范围和分配顺序的…     

浅析成本会计中的分配问题

成本会计中的基础理论部分,可以简单的归结为关于各项要素费用及各个成本项目的归集与分配。其中,归集是目的,分配是手段,分配是为了更好地归集。所以,分配即是重点,又是难点。但由于其中的分配方法很多,计算又比较复杂,多数学生学起来有一定难度。本文通过分析分配的概念、分配的基本思路并结合举例来说明诸多分配方法的一些共性和规律,希望对学生进行成本会计的学习有所帮助。     

A genetic algorithm for the partial binary constraint satisfaction problem: an application to a frequency assignment problem

We describe a genetic algorithm for the partial constraint satisfaction problem. The typical elements of a genetic algorithm, selection, mutation and cross-over, are filled in with combinatorial ideas. For instance, cross-over of two solutions is performed by taking the one or two domain elements in the solutions of each of the variables as the complete domain of the variable. Then a branch-and-bound method is used for solving this small instance. When tested on a class of frequency assignment problems this genetic algorithm produced the best known solutions for all test problems. This feeds the idea that combinatorial ideas may well be useful in genetic algorithms.     

Expatriate pay satisfaction: the role of organizational inequities,assignment stressors and perceived assignment value

Using equity, stress and buffer theories, we investigate the role played by organizational inequities (organizational justice and provision of benefits) and assignment stressors (work adjustment and role novelty) in predicting expatriate pay satisfaction. We also assess the role of perceived assignment value as an important buffer that moderates the above relationships. With a sample of 78 expatriates from nine nationalities working in Hong Kong, we find that organizational justice and work adjustment are both positively related to expatriate pay satisfaction. We also find that perceived assignment value strengthens the provision of benefits–pay satisfaction and work adjustment–pay satisfaction relationships. Limitations and managerial implications are discussed.     

Consistency in the probabilistic assignment model

This paper introduces a notion of consistency for the probabilistic assignment model, which we call probabilistic consistency. We show that the axioms equal treatment of equals and probabilistic consistency characterize the uniform rule, which is the rule which randomizes uniformly over all possible assignments.     

Testing random assignment to peer groups

Identification of peer effects is complicated by the fact that the individuals under study may select their peers. Random assignment to peer groups has proven useful to sidestep such a concern. In the absence of a formal randomization mechanism, it needs to be argued that assignment is “as good as” random. This paper introduces a simple yet powerful test to do so. We provide theoretical results for this test. As a by-product, we equally obtain such results for an approach popularized by Guryan et al. (2009). These results help to explain why this approach suffers from low power, as has been observed elsewhere.     

Dynamic incentive effects of assignment mechanisms: Experimental evidence

Optimal assignment and matching mechanisms have been the focus of exhaustive analysis. We focus on their dynamic effects, which have received less attention, especially in the empirical literature: Anticipating that assignment is based on prior performance may affect prior performance. We test this hypothesis in a lab experiment. Participants first perform a task individually without monetary incentives; in a second stage, they are paired with another participant according to a pre‐announced assignment policy. The assignment is based on the first‐stage performance, and compensation is determined by average performance. Our results are largely consistent with a theory: Pairing the worst‐performing individuals with the best yields 20% lower first‐stage effort than random matching (RAM) and does not induce truthful revelation of types, which undoes any policy that aims to reallocate types based on performance. Perhaps surprisingly, however, pairing the best with the best yields only 5% higher first‐stage effort than RAM and the difference is not statistically significant.     

信息系统安全性分析与设计

文章针对以往信息管理系统安全管理中所出现的弊端,提出了一种基于岗位角色的用户权限控制管理的方法。该方法描述了用户、岗位角色和权限的关系,通过分配和取消岗位角色来完成用户权限的控制,较好地解决了系统用户权限管理方面的问题。     

Signed social structure optimization for shift assignment in the nurse scheduling problem

This paper develops a mathematical framework that relies on modern social network analysis theories for treating the nurse team formation and nurse scheduling (shift assignment) problems, accounting for signed social connections. These problems lie in assigning nurses to teams/shifts such that the constraints regarding both the working regulations and nurses preferences are satisfied. Recent research indicates the dependence of nursing team performance on team social structure; however, so far, the social structure considerations have not been explicitly incorporated into the mathematical formulations of the nurse scheduling problem. The presented framework introduces models that quantitatively exploit such dependence. This paper explores instances of Nurse Team Formation Problem (NTFP) and Nurse Scheduling Problem (NSP) incorporating signed social structure with the measures based on such network structures as edges, full dyads, triplets, k-stars, balanced and unbalanced triangles, etc., in directed, signed networks. The paper presents the integer programming formulations for NTFP and NSP, and a problem-specific heuristic that performs variable-depth neighborhood search to tackle NTFP instances with signed social structures. Computational results for a real-world problem instance with 20 nurses are reported. The insights obtained from the presented framework and future research directions are discussed.     

网格环境中基于GSI的改进授权模型的设计

网格计算作为一种新的分布式计算模型,具有分布式、异构和动态变化等特性,若要在网格中实现资源共享的目的,资源的访问控制是首当其冲需要解决的问题。网格的访问控制是建立在现有的基于角色访问控制系统之上的,但是由于网格跨越多个不同的地点和不同的自治域,每个域的访问控制策略和需求可能相差甚远,这使得资源的访问控制更加复杂,如用户-角色的指派和映射。文章在现有的GSI改进授权模型中,用属性对角色进行了扩展,可实现更灵活、动态和细粒度的访问控制。     

On the assignment of students to topics: A Variable Neighborhood Search approach

This article presents a study of a practical assignment problem found in teaching within higher education. Here, students are assigned to scientific topics for which written papers must be submitted. Often, preferences across topics exist among other side constraints that should be considered in solving the problem of interest. Characterizing attributes of real-world problems were studied for scientific departments in Economics and Business Administration at German universities by sending out 800 questionnaires, and analyzing the 203 responses.Based on earlier studies, a Variable Neighborhood Search (VNS) approach was formulated to solve the resulting assignment problem. Several neighborhood search operators were tested, and numerical results are reported for a range of problem scenarios taken from real-world cases. It was observed that VNS leads to superior results vs. single operator local search approaches. Furthermore, we were able to show that in the studied problem, the effectiveness of certain neighborhoods was, to a large extent, dependent on the structures of the underlying problem.An extension of the problem was formulated by integrating a second objective function, which simultaneously balances the workload of staff members while maximizing student utility. The VNS approach was implemented in a computer system, available free of charge, providing decision support for selected other institutions within higher education.