Sequential resource allocation with constraints: Two-customer case

We study a two-customer sequential resource allocation problem with equity constraint, which is reflected by a max–min objective. For finite discrete demand distribution, we give a sufficient and necessary condition under which the optimal solution has monotonicity property. However, this property never holds with unbounded discrete distribution.     

A possible human counterpart of the principle of increasing entropy

It is well-known that the principle of increasing entropy holds for isolated natural systems that contain non-adaptive molecules. Here we present, for the first time, an experimental evidence for a possible human counterpart of the principle in an isolated social system that involves adaptive humans. Our work shows that the human counterpart is valid even though interactions among humans in social systems are distinctly different from those among molecules in natural systems. Thus, it becomes possible to understand social systems from this natural principle, at least to some extent.     

Mobile relays for enhanced broadband connectivity in high speed train systems

With the introduction of wireless modems and smart phones, the passenger transport industry is witnessing a high demand to ensure not only the safety of the trains, but also to provide users with Internet access all the time inside the train. When the Mobile Terminal (MT) communicates directly with the Base Station (BS), it will experience a severe degradation in the Quality of Service due to the path loss and shadowing effects as the wireless signal is traveling through the train. In this paper, we study the performance in the case of relays placed on top of each train car. In the proposed approach, these relays communicate with the cellular BS on one hand, and with the MTs inside the train cars on the other hand, using the Long Term Evolution (LTE) cellular technology. A low complexity heuristic LTE radio resource management approach is proposed and compared to the Hungarian algorithm, both in the presence and absence of the relays. The presence of the relays is shown to lead to significant enhancements in the effective data rates of the MTs. In addition, the proposed resource management approach is shown to reach a performance close to the optimal Hungarian algorithm.     

An approach to find redundant objective function(s) and redundant constraint(s) in multi-objective nonlinear stochastic fractional programming problems

Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in constraints and variables are usually studied in a class of mathematical programming problems. However, main emphasis has so far been given only to linear programming problems. In this paper, an algorithm that identifies redundant objective function(s) and redundant constraint(s) simultaneously in multi-objective nonlinear stochastic fractional programming problems is provided. A solution procedure is also illustrated with numerical examples. The proposed algorithm reduces the number of nonlinear fractional objective functions and constraints in cases where redundancy exists.     

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。     

The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network

Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems.     

基于风险-均值分析的供应商选择与订单分配集成优化模型与求解

针对不确定环境下具有不同供应合约的供应商选择与订单分配问题,本文构建了基于风险-均值分析的模糊两阶段多周期集成优化模型。与传统的该问题研究并未充分考虑供应商选择与订单分配两阶段决策的交互影响不同,在该模型中,第一阶段供应商选择的评价目标依赖于后期实际运营中的订单分配决策;并考虑未来需求和实际运营成本的不确定性,引入在险价值和期望值两种决策准则对供应商选择方案的绩效进行评价。提出了该模型的分析求解方法,在险价值得以精确评估,期望值被控制在确定的误差范围内,并可以达到足够的精度要求。