能量收集无线网络中面向统计服务质量的最优功率分配

针对能量收集无线网络中的服务质量（QoS）保障问题,提出了面向统计QoS的最优功率分配方案,从而最大化时延QoS约束下的有效容量。首先,构建能量收集无线网络的有效容量最大化问题。其次,利用凸优化理论求解出最优功率分配方案以及该方案下的最大有效容量,并得出了两种特例下的最优功率分配方案,即：当QoS需求非常松弛时,最优化功率分配方案收敛于注水策略;当QoS需求非常严格时,最优化功率分配方案收敛于信道反转策略。然后,求解了所提最优功率分配方案得到的信道中断概率。最后,通过仿真实验,检验了该最优功率分配方案的性能。实验结果表明,与现有策略相比,所提方案能够获得更大的有效容量。     

无人机辅助无线通信网络资源自适应协同分配

为保证边缘用户可正常使用通信网络资源,研究了无人机辅助的无线通信网络资源自适应协同分配技术。构建无人机辅助无线通信网络模型,并设置自适应协同分配的目标函数,从而进行网络资源最大化的资源分配。引入排斥、吸引方法改进果蝇算法,提取最优、最差味道浓度与坐标信息。输出资源的最优传输速率、最优无人机运行轨迹的分配解,改进求解资源分配目标函数,完成通信网络资源自适应协同分配。试验结果表明,不同工况中,无人机能够结合用户分布状态飞行。在用户最小速率需求标准依次是3 bit/s、6 bit/s、9 bit/s时,经过6次迭代,算法便可收敛到纳什均衡点,无线通信任务时延便可控制为最小值1.5 s。该技术能够自适应协同分配无人机辅助无线通信网络资源。协同分配结果满足用户需求。     

基于移位加速和TCAM的高速多模式匹配算法

在研究流行的多模式匹配实现方案的基础上,利用TCAM实现高速、并行查找,提出一个基于TCAM的多模式匹配改进算法。该算法通过对模式的移位加速和移动步长的灵活控制,使平均移动步长得到很大提高。实验表明,在TCAM位宽为8 Byte的情况下,该算法使平均移动步长由1 Byte增加到5 Byte,匹配速率也由2 Gb/s增加到10 Gb/s。     

基于FPGA的50GMII设计与实现

为提高通信网络设备中以太网接口的带宽能力，需要提升以太网媒体独立接口（Media Independent Interface,MII）的数据转换效率。利用FPGA可实现硬件加速的优点，通过拓展接口数据位宽和提高时钟频率的方法，采用多模块并行计算处理模式，设计实现具有50 Gbit/s的MII模块（50GMII）。相较已有的10 Gbit/s以太网MII规范，所设计的接口数据位宽发生改变，在提高整体模块数据转换效率的同时，可以保证时钟频率不至于大幅提高，有利于设计模块的稳定性，高位宽数据的组帧转换处理成为本设计的重点。实践表明，该方法能够正确实现以太网用户侧和线路侧的数据格式转换，并达到50 Gbit/s数据吞吐速率，具有较强的实用性。     

多选择背包问题离散狼群算法研究

狼群算法是一种通过模拟狼群的捕食行为和猎物分配方式提出的群体智能算法,为求解复杂组合优化问题提供了一种新的思路。目前狼群算法不能解决离散问题,以NP难中的经典问题——多选择背包问题的求解为研究对象,设计了基于离散空间的狼群算法。对于离散空间的狼群算法,通过将人工狼编码,重新设计了狼群的游走、奔袭和围捕过程,并设计了三个过程中的步长。把学习机制引入离散狼群算法,实现了人工狼之间的交流,且确立了自适应步长公式。结果表明：离散狼群算法成功实现了对离散问题的求解,为组合优化问题的求解提供了新方法。     

改进细菌觅食算法求解车间作业调度问题*

针对细菌觅食算法（BFOA）求解高维优化问题时容易陷入局部最优和早熟的问题,引入自适应步长及差分进化算子,并将改进算法用于车间作业调度问题（JSP）中。求解时,设计了一种编码转换方案,从而无须修改BFOA运算规则即可实现对JSP的寻优;同时,采用空闲时间片段优化策略降低了调度问题的复杂性。仿真实验表明,该算法能够跳出局部最优,避免了早熟的问题,调度结果优于原始细菌觅食算法和离散粒子群算法。     

基于优化缓存模型的IPQAM频点管理方法研究

针对已有基于缓存策略的IPQAM（边缘调制器）频点管理方法中响应速率有待进一步提高、响应时延较大等问题, 提出了一种基于优化缓存模型的IPQAM频点管理方法。该优化缓存模型的设计充分考虑了IPQAM频点资源、频点端口资源, 以及资源所在服务组之间的关联关系, 模型中只加载资源的部分属性, 以降低对系统内存的消耗。基于该优化缓存模型, 设计并实现了一种IPQAM频点分配、回收方法, 该方法充分利用该优化缓存模型的结构优势, 能够快速完成目标资源的定位, 具备较优的平均时间复杂度。仿真实验表明, 与同类方法相比, 该方法能够以更低的响应时延(0. 02~0. 04 ms)提供更高的响应速率(最高16 000次/s), 在管理资源数量方面, 具备很好的系统可伸缩性。     

电动汽车分时租赁用户预约分配问题的新型电磁场优化算法求解

针对电动汽车电量对于行驶里程的限制问题,建立用户预约分配模型,以得到利润最大时的订单分配结果。该类问题属于NP-hard问题,求解具有一定困难。因此,设计一种新型离散电磁场优化算法求解方法。在基本电磁场优化算法的基础上使用二进制编码方式,改变粒子移动方式,并对负电磁场中的电磁粒子增加更新过程。将提出的新算法与遗传算法、二进制粒子群算法、改进二进制布谷鸟算法及二进制狮群算法进行对比,数值实验表明新算法具有更高的计算效率。此外,与传统分配模型相比,新订单分配模型能够获得更高的利润,说明了该模型的有效性。     

自适应变步长迭代动态规划方法及其在间歇过程优化中的应用

迭代动态规划(IDP) 作为一种求解非线性问题的离散算法, 其寻优精度和收敛速度受到时间段划分的影响. 通常, 时间段划分依赖主观经验, 缺乏科学有效的指导. 针对终端时刻固定的动态优化问题, 提出一种自适应变步长IDP 算法, 综合考虑控制变量与目标函数值的变化, 对时间段数量、长度和切换点进行优化. 将该方法应用于间歇过程优化, 结果表明其能够智能分配时间段数量与长度, 可有效提升寻优精度.

     

基于比例公平的多用户MIMO-OFDM系统自适应资源分配算法*

针对传统多用户MIMO-OFDM系统中自适应资源分配算法计算复杂度较高、实时性不强、无法保证用户间公平性等问题,提出了一种低复杂度的自适应子载波、比特及功率分配算法。在子载波分配上,该算法能够在兼顾比例速率约束的前提下使系统发射功率达到最小化;在比特及功率分配上,该算法将非线性优化问题转换为线性优化问题,在保证系统性能的同时显著降低计算量。仿真结果表明,该算法具有良好的性能,能够有效降低计算量,并使系统容量在用户间分配得更加公平和合理。     

基于PCI Express的高速数据传输系统研究与开发

为了解决高速数据采集系统中的数据传输速率这一瓶颈问题,在对PCI Express总线进行研究后,提出了一种基于PCI Express总线的高速数据传输系统的构建方法;系统设计中采用模块化的设计思想,探讨了PCI Express软件层的设计思路和实现方法,阐述了各个模块的功能,最后对编写PCI Express设备驱动程序的几个关键问题进行了论述并给出解决方案;采用以上设计方法,系统运行稳定可靠,目前已实现2.5Gbit/s的数据传输速率,对系统进行改进可获得5Gbit/s、10Gbit/s甚至更高的数据传输速率.     

Optimal capacity allocation for Web systems with end-to-end delay guarantees

Providing quality of service guarantees have become a critical issue during the rapid expansion of the e-Commerce area. We consider the problem of finding the optimal capacity allocation in a clustered Web system environment so as to minimize the cost while providing the end-to-end performance guarantees. In particular, we consider constraints on both the average and the tail distribution of the end-to-end response times. We formulate the problem as a nonlinear program to minimize a convex separable function of the capacity assignment vector. We show that under the mean response time guarantees alone, the solution has a nice geometric interpretation. Various methods to solve the problem are presented in detail. For the problem with tail distribution guarantees, we develop an approximation method to solve the problem. We also derive bounds and show that the solution is asymptotically optimal when the service requirement becomes stringent. Numerical results are presented to further demonstrate the robustness of our solutions under data uncertainty.     

A differential evolution algorithm to solve redundancy allocation problems

To improve system reliability without changing its nature, three methods are proposed. The first method uses more reliable components and the second method provides redundant components within the system. The third method is a combination of these two methods. The redundancy allocation problem (RAP) finds the appropriate mix of components and redundancies within a system to maximize its reliability or minimize its cost due to several constraints, such as cost, weight, and volume. This paper presents a methodology to solve the RAP, which is an NP‐hard problem, modeled with discrete variables. In this paper, we use a metaheuristic to solve the RAP of a series–parallel system with a mix of components. Our metaheuristic offers a practical method with specific solution encoding, and combines a penalty function to solve large instances of the relaxed RAP, where different types of components can be used in parallel. The efficiency of the algorithm was tested through a set of well‐known benchmark problems from the literature. Testing of the algorithm achieved satisfactory results in reasonable computing time.     

港口拖轮优化配置研究

研究港口拖轮数量及马力的合理配置问题,传统的机械设备优化配置方法大都采用单纯的数学模型来解决,但该方法在实际应用中附加条件较多,而且复杂系统的数学模型难以建立.拖轮作业过程是一个离散的、动态的、随机过程,难以用确定性的数学模型来进行描述,通过分析港口拖轮作业的过程及其特点,利用离散系统仿真技术模拟复杂的拖轮的作业过程,采用面向事件的离散系统仿真策略,开发了一套可用于解决港口拖轮优化配置的计算机仿真系统,最后为了验证整个系统的可行性,拟定了不同拖轮配置方案进行仿真运行,得出在不同配置方案下拖轮的利用率和港口的服务性能,结合模糊决策的优化方法,选择港口拖轮的最优配置方案,该方案可为港口拖轮的优化配置提供科学合理的决策支持.     

An integer programming column generation principle for heuristic search methods

There is an increasing interest in integrating column generation and heuristic approaches to efficiently solve large‐scale discrete optimisation problems. We contribute in this direction. Based on the insights from Lagrangian duality theory, we present an auxiliary problem that can be used for finding near‐optimal solutions to a discrete column‐oriented model. The structure of this auxiliary problem makes it suitable for being addressed with a heuristic search method involving column generation. To this end, we suggest a large neighbourhood search strategy where the repair step is to solve a column generation type subproblem. The suggested search strategy and mathematical models involved need to be tailored to the problem structure. To illustrate important design options and computational behaviour, four applications are studied: bin packing, generalised assignment, a resource allocation problem and the fixed‐charge transportation problem.     

Dynamic vehicle allocation control for automated material handling system in semiconductor manufacturing

The current study examines the dynamic vehicle allocation problems of the automated material handling system (AMHS) in semiconductor manufacturing. With the uncertainty involved in wafer lot movement, dynamically allocating vehicles to each intrabay is very difficult. The cycle time and overall tool productivity of the wafer lots are affected when a vehicle takes too long to arrive. In the current study, a Markov decision model is developed to study the vehicle allocation control problem in the AMHS. The objective is to minimize the sum of the expected long-run average transport job waiting cost. An interesting exhaustive structure in the optimal vehicle allocation control is found in accordance with the Markov decision model. Based on this exhaustive structure, an efficient algorithm is then developed to solve the vehicle allocation control problem numerically. The performance of the proposed method is verified by a simulation study. Compared with other methods, the proposed method can significantly reduce the waiting cost of wafer lots for AMHS vehicle transportation.     

Optimal allocation and maintenance of multi-state elements in series–parallel systems with common bus performance sharing

This article considers the optimal allocation and maintenance of multi-state elements in series–parallel systems with common bus performance sharing. The surplus performance from a sub-system can be transmitted to any other sub-system which is experiencing performance deficiency. The amount that can be transmitted is subjected to a random transmission capacity. In order to increase the system availability, maintenance actions can be performed during the system lifetime and the system elements can be optimally allocated into the sub-systems. In this paper, we consider the element allocation and maintenance simultaneously in order to minimize the total maintenance cost subject to the pre-specified system availability requirement. An algorithm based on universal generating function is suggested to evaluate the system availability and the genetic algorithm is explored to solve the optimization problem. Numerical experiments are presented to illustrate the applications.     

OFDM系统自适应资源算法研究

针对OFDM系统的比特功率自适应分配优化问题。因传输信道存在衰减率,误码等,提出了一种基于遗传算法的OFDM系统自适应比特功率分配算法。新算法定义了染色体和初始群体,并通过遗传算法中的交叉、变异等操作,使比特功率分配方案得到全局最优解。算法可通过确定不同的适应度函数,用于解决传输速率及误码率一定条件下使得总发送功率最小的比特功率达到最优化的目的。通过上述在运算复杂度等方面的性能的仿真,证明优于Hughes-Hartogs等几种传统算法。     

Hybrid approach for buffer allocation in open serial production lines

The buffer allocation problem is an NP-hard combinatorial optimization problem involving the determination of the number of buffers in buffer locations required to increase the efficiency of a production line. Researchers in this field have proposed various optimization techniques to solve the problem for different types of production system configurations. In this study, a hybrid approach-based simulation optimization is proposed to determine the buffer sizes required in open serial production lines to maximize the average production rate of the system. This approach involves the use of a search tool and an evaluative tool. A hybrid approach using a genetic algorithm and simulated annealing is used as a search tool to create candidate buffer sizes. As an evaluative tool, discrete event simulation modeling is used to obtain the average production rate of the line. The performance of the proposed approach and the power of the hybridization are investigated for various serial line configurations. Promising results demonstrate the efficacy of the proposed hybrid approach for the buffer allocation problem in open serial lines.