Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

Approximate steady-state analysis of large Markov models based on the structure of their decision diagram encoding

We propose a new approximate numerical algorithm for the steady-state solution of general structured ergodic Markov models. The approximation uses a state-space encoding based on multiway decision diagrams and a transition rate encoding based on a new class of edge-valued decision diagrams. The new method retains the favorable properties of a previously proposed Kronecker-based approximation, while eliminating the need for a Kronecker-consistent model decomposition. Removing this restriction allows for a greater utilization of event locality, which facilitates the generation of both the state-space and the transition rate matrix, thus extends the applicability of this algorithm to larger and more complex models.     

基于高边电流检测驱动LED

研究了一种采用高边电流检测的滞环控制LED恒流驱动芯片。基于0．5um5V／18V／40VCDMOS．工艺,运用HSPICE工具对电路进行仿真,仿真结果显示：在4．5V～28V电源电压范围内,-40℃～＋l25℃工作温度范围内,电路可为LED提供恒定的350mA驱动电流,LED驱动电流为滞环变化的三角波,最大误差为6．2％。通过调节外部信号DIM的占空比可以调节LED的亮度。     

Efficient Tate pairing computation using double-base chains

Pairing-based cryptosystems have developed very fast in the last few years. The efficiencies of these cryptosystems depend on the computation of the bilinear pairings, In this paper, a new efficient algorithm based on double-base chains for computing the Tate pairing is proposed for odd characteristic p 〉 3. The inherent sparseness of double-base number system reduces the computational cost for computing the Tate pairing evidently. The new algorithm is 9% faster than the previous fastest method for the embedding degree k = 6.     

On the Convergence of Temporal-Difference Learning with Linear Function Approximation

The asymptotic properties of temporal-difference learning algorithms with linear function approximation are analyzed in this paper. The analysis is carried out in the context of the approximation of a discounted cost-to-go function associated with an uncontrolled Markov chain with an uncountable finite-dimensional state-space. Under mild conditions, the almost sure convergence of temporal-difference learning algorithms with linear function approximation is established and an upper bound for their asymptotic approximation error is determined. The obtained results are a generalization and extension of the existing results related to the asymptotic behavior of temporal-difference learning. Moreover, they cover cases to which the existing results cannot be applied, while the adopted assumptions seem to be the weakest possible under which the almost sure convergence of temporal-difference learning algorithms is still possible to be demonstrated.     

Towards More Complete Models of TCP Latency and Throughput

Recently, several researchers have developed equations for modeling TCP behaviors, such as the expected throughput or latency, based on Markov chains derived from TCP with additional simplifying assumptions. In this paper, we suggest new directions for Markov chain analyses of TCP. Our first contribution is to closely examine not just the expectation but the entire cumulative distribution function of transfer times under various models. Particularly for short or medium transfers, the distribution is likely to be more useful than the expectation in terms of measuring end-user satisfaction. We find that the shapes of TCP cumulative distribution functions are remarkably robust to small changes in the model. Our results suggest that simplifying Markov analyses can be extended to yield approximations for the entire distribution as well as for the expectation.Our second contribution is to consider correction procedures to enhance these models. A correction procedure is a rule of thumb that allows equations from one model to be used in other situations. As an example, several analyses use a Drop-Tail loss model. We determine correction procedures for the deviation between this model and other natural loss models based on simulations. The existence of a simple correction procedure in this instance suggests that the high-level behavior of TCP is robust against changes in the loss model.     

Efficient simulated annealing on fractal energy landscapes

We present a new theoretical framework for analyzing simulated annealing. The behavior of simulated annealing depends crucially on the ldergy landscape associated with the optimization problem: the landscape must have special properties if annealing is to be efficient.We prove that certain fractal properties are sufficient for simulated annealing to be efficient in the following sense: If a problem is scaled to have best solutions of energy 0 and worst solutions of energy 1, a solution of expected energy no more than can be found in time polynomial in 1/, where the exponent of the polynomial depends on certain parameters of the fractal. Higher-dimensional versions of the problem can be solved with almost identical efficiency.The cooling schedule used to achieve this result is the familiar geometric schedule of annealing practice, rather than the logarithmic schedule of previous theory. Our analysis is more realistic than those of previous studies of annealing in the constraints we place on the problem space and the conclusions we draw about annealing's performance.The mode of analysis is also new: Annealing is modeled as a random walk on a graph, and recent theorems relating the conductance of a graph to the mixing rate of its associated Markov chain generate both a new conceptual approach to annealing and new analytical, quantitative methods.The efficiency of annealing is compared with that of random sampling and descent algorithms. While these algorithms are more efficient for some fractals, their run times increase exponentially with the number of dimensions, making annealing better for problems of high dimensionality.We find that a number of circuit placement problems have energy landscapes with fractal properties, thus giving for the first time a reasonable explanation of the successful application of simulated annealing to problems in the VLSI domain.This work was done while the author was on leave from IBM Research, and was also sponsored by DARPA and monitored by SNWSC under contract numbers N00039-87-C-0182 and N00039-88-C-0292. The author is completing his doctoral studies with Prof. Alberto Sangiovanni-Vincentelli. He is on leave from the I.B.M. Thomas J. Watson Research Center.     

基于改进期望最大化算法的分布式视频编码

目前,分布式视频编码（DVC）由于具有低复杂编码特性而成为视频编码领域的研究热点。DVC中,边信息性能对系统性能影响很大,一般而言,边信息性能越好,则整个系统压缩性能越好。本文研究了一种基于贝叶斯准则的期望最大化（Expectation Maximization,EM）边信息产生方法,并从运动搜索模板和初始概率模型两方面对EM算法提出了改进。实验表明,在几乎相同的率失真性能下,两种改进算法的学习时间分别缩短了30%和16%。     

基于ROI运动区域的分布式视频编码方法

传统的分布式视频编码方法中,视频帧的解码通常采用内插或外推的方法,然而对于运动剧烈视频帧的解码效果却并不理想,会产生重影、鬼脸等现象.因此,提出了一种基于ROI运动区域的分布式视频编码解决方案,通过在编码端提取ROI辅助信息,然后在解码端将其与边信息做融合处理来得到更加准确的边信息,从而提高视频解码的质量.实验结果表明,与传统的分布式视频编码方法相比,基于ROI运动区域的分布式视频编码解决方案在性能上平均有3.1db的提高.     

一种竹丝正反面辨识传感器及其辨识方法

为了解决竹席编织自动送丝系统中准确区分原料竹丝正反面的问题,设计了一种竹丝正反面辨识传感器。传感器机械结构与竹丝反面中心凹槽构成光通道,红外光经过该光通道传播至红外光敏三极管,通过检测三极管的c-e极电流可测得红外线的光通量,进而识别出竹丝的正反两面。此外,还研究了单个传感单元对竹丝正反两面输出电流的分布曲线,并给出了一种同质多传感单元条件下的融合策略。经实验,该传感器能快速准确地识别原料竹丝的正反面,为实现竹席编织自动送丝系统提供了基础。