Optimal assets allocation and benefit outgo policies of DC pension plan with compulsory conversion claims

In this paper, we study optimal asset allocation and benefit outgo policies of DC (defined contribution) pension plan. We extend He and Liang model (2013a,b) to describe dynamics of individual fund scale during distribution period. The fund scale is affected by investment return, benefit outgo and mortality credit. The management of the pension plan controls the asset allocation and benefit outgo policies to achieve the objective of pension members. The goal of the management is to minimize accumulated deviations between the actual benefit outgo and a pre-set target during the whole distribution period. The performance function (criterion) is the weighted average of the square and linear deviations to express more penalty on negative deviation than positive deviation. Using HJB (Hamilton–Jacobi–Bellman) equations and variational inequality methods, the closed-forms of the optimal policies are derived. The counterintuitive effect of the optimal proportion allocated in the risky asset with respect to the fund scale is also derived, and the optimal benefit outgo has the form of the spread method. Moreover, we use Monte Carlo Methods (MCM) to analyze economic behaviors of the optimal asset allocation and benefit outgo policies.     

一种基于STM32的NAND flash的块分配框架设计

STM32对大容量数据文件存储与管理问题可通过NAND flash来解决。而NAND flash的高效管理需要文件系统参与。NAND flash有特殊的块读写及擦除机制,一般的嵌入式文件系统组织结构并不完全兼容NAND flash。针对NAND flash的特点兼顾STM32的资源承受力要提出新的NAND flash块分配框架,框架通过块分配槽这种数据结构,在不使用块分配表与垃圾表的情况下,实现了NAND flash均衡负载与垃圾块的回收;同时通过节点分配栈与文件节点表的配合来提高STM32对文件的读写速度,空间利用率和系统性能。仿真实验和计算结果表明该块分配框架可有效提高NAND flash块的均衡负载与节省RAM空间。     

基于MetropolisQ学习的蜂窝网络在线信道分配

针对现有的蜂窝网络的在线动态分配模型具有的信道需求量大、呼叫动态变化时阻塞率高和收敛速度慢的缺点,设计了一种基于MetropoisQ学习的蜂窝网络的在线信道分配方法。首先,在考虑同信道限制、邻居信道限制和同小区限制的基础上,设计了在线信道分配的数学模型,然后在Q-Learning算法基础上的设计了一种基于资格迹的Q(λ)算法实现信道的在线分配,为了进一步提高收敛速度,采用Metropois规则对算法中动作的选择方式进行改进,实现探索和利用的平衡。为了验证文中方法,采用Matlab工具上进行实验,仿真实验结果表明文中方法能实现蜂窝通信网络的在线信道分配,且与其它方法比较,具有较少的信道需求量、较低的阻塞率和收敛速度,较其它方法具有较大优越性。     

基于生命期模型的无线传感器网络信道分配博弈算法

针对无线传感器网络中节点因干扰过大导致重传能耗增加, 进而节点过早失效、网络生命期缩短的问题, 根据网络拓扑信息和路由信息设计节点的负载模型, 从而构建了节点的生命期模型. 然后利用博弈论将路径增益、交叉干扰和节点生命期等性能参数融入到效益函数中, 构建信道分配博弈模型. 理论分析证明该博弈模型存在纳什均衡. 进而运用最佳回应策略, 在所构建的信道分配博弈模型的基础上, 设计了一种优化网络生命期的抗干扰信道分配算法. 该算法使节点在选择信道时避免与网络中交叉干扰较大的节点和生命期较小的节点使用相同信道, 实现干扰小、能耗低且均衡的信道选择. 理论分析与仿真结果证明该算法最终能够快速地收敛到纳什均衡, 且具有较小的信息复杂度, 从而减小算法本身的通信能耗. 同时, 该算法具有良好的抗干扰性和信道均衡性, 能够有效地延长网络生命期.     

Allocating fixed costs and common revenue via data envelopment analysis

An issue of considerable importance involves the allocation of fixed costs or common revenue among a set of competing entities in an equitable way. Based on the data envelopment analysis (DEA) theory, this paper proposes new methods for (i) allocating fixed costs to decision making units (DMUs) and (ii) distributing common revenue among DMUs, in such a way that the relative efficiencies of all DMUs remain unchanged and the allocations should reflect the relative efficiencies and the input-output scales of individual DMUs. To illustrate our methods, numerical results for an example are described in this paper.     

基于统一价格拍卖的初始排污权分配方法

针对初始排污权总量分配的实际问题,基于统一价格拍卖的思想提出了一种具有激励性的可变总量的分配方法,分别给出了排污企业对称和排污企业非对称两种情形下的线性均衡报价策略,并证明了该方法的可行性和有效性,从而为建设排污权分配和交易制度提供了理论依据和方法参考.     

混沌量子克隆算法求解认知无线网络频谱分配问题

对认知无线网络中的频谱进行有效分配是实现动态频谱接入的关键技术.考虑3次用户对频谱的需求和分配的公平性,给出了频谱分配的数学模型,并将其转换为以最大化网络收益为目标的带约束优化问题,进而提出一种采用混沌量子克隆优化求解的认知无线网络频谱分配算法, 并证明了该算法以概率1收敛.最后,通过仿真实验比较了本文算法与颜色敏感图着色算法、基于遗传算法的频谱分配、基于量子遗传算法的频谱分配的性能.结果表明:本文算法性能较优, 能更好地实现网络收益最大化. 关键词： 混沌量子克隆算法 认知无线网络 频谱分配     

纳税最优的工资奖金分配方案研究

根据我国现行的税法,个人所得税纳税采用九级累进税率.年工资和年终奖在速算扣除数个数上存在不同,使得对于相同的税前年收入,如果采用不同的年工资和年终奖分配方案会产生不同的税后实际所得.通过简化变量和缩小有效解区域,以及一系列严格的数学推导,得到了任意年收入下,月工资和年终奖的最优分配方案,使得在现有税制下,纳税额最小,税后收入最大.这个最优方案避免了税金负效应现象,保证了纳税公平性,有利于国家税务监管,企业员工薪金分配和个人纳税筹划;具有广阔的应用前景.     

Trade-offs between target hardening and overarching protection

Defenders concerned about protecting multiple targets can either protect them individually (through target hardening), or collectively (through overarching protections such as border security, public health, emergency response, or intelligence). Decision makers may find it relatively straightforward to choose which targets to harden, but are likely to find it more difficult to compare seemingly incommensurate forms of protection - e.g., target hardening, versus a reduction in the likelihood of weapons being smuggled across the border. Unfortunately, little previous research has addressed this question, and fundamental research is needed to provide guidance and practical solution approaches. In this paper, we first develop a model to optimally allocate resources between target hardening and overarching protection, then investigate the factors affecting the relative desirability of target hardening versus overarching protection, and finally apply our model to a case study involving critical assets in Wisconsin. The case study demonstrates the value of our method by showing that the optimal solution obtained using our model is in some cases substantially better than the historical budget allocation.     

A survey of berth allocation and quay crane scheduling problems in container terminals

Due to the variety of technical equipments and terminal layouts, research has produced a multitude of optimization models for seaside operations planning in container terminals. To provide a support in modeling problem characteristics and in suggesting applicable algorithms this paper reviews the relevant literature. For this purpose new classification schemes for berth allocation problems and quay crane scheduling problems are developed. Particular focus is put on integrated solution approaches which receive increasing importance for the terminal management.