Improved algorithms for resource allocation under varying capacity

We consider the problem of scheduling a set of jobs on a system that offers certain resource, wherein the amount of resource offered varies over time. For each job, the input specifies a set of possible scheduling instances, where each instance is given by starting time, ending time, profit and resource requirement. A feasible solution selects a subset of job instances such that at any timeslot, the total requirement by the chosen instances does not exceed the resource available at that timeslot, and at most one instance is chosen for each job. The above problem falls under the well-studied framework of unsplittable flow problem on line. The generalized notion of scheduling possibilities captures the standard setting concerned with release times and deadlines. We present improved algorithms based on the primal–dual paradigm, where the improvements are in terms of approximation ratio, running time and simplicity.     

A Voltage Phasor Based Fault-classification Method for Phasor Measurement Unit Only State Estimator Output

Abstract—This article presents a fault-classification method for transmission lines based on voltage phasors using classification and regression trees. The proposed method is intended to aid system operators in understanding the outputs of a phasor measurement unit only state estimator. Faults are classified into four categories when the estimator is positive sequence and into ten categories when the estimator is three phase. The fault data are generated in PowerWorld® (PowerWorld Corporation, Champaign, IL, USA) and DSA Tools® (Powertech Labs Inc., Surrey, British Columbia, Canada). The pre-fault state consists of a variety of operating conditions and loading angles of faulted lines. The fault condition comprises different fault types, fault locations, fault impedances, and fault incidence angles. Fault classification is done using MATLAB® (The MathWorks, Natick, Massachusetts, USA).The approach is successfully tested on the IEEE-118 bus system. The results demonstrate that the technique developed here is effective and robust, irrespective of the pre-fault and fault conditions.     

Minimization of quantization noise amplification in biorthogonal subband coders

Quantization noise amplification (QNA) restricts the coding gain (CG) in biorthogonal subband coders. Here, a coloring filter is introduced to color the quantization noise. The optimal coloring filter eliminating/minimizing QNA, with or without order restriction, is found for a given finite-impulse response filter bank (FB). An efficient implementation of the coloring filter is proposed. With the coloring filter, the optimal biorthogonal ideal FB becomes the full whitening coder achieving maximum possible CG. Results verify the CG improvement due to coloring for existing FBs.     

BOT's based on nonuniform filter banks

Parallels between orthogonal transforms and filter banks have been drawn before. Block orthogonal transform (BOT) is a special case of orthogonal transform where a nonoverlapping window is used. We relate BOTs to filter banks. Specifically, we show that any BOT can be shown as a perfect reconstruction filter bank, and any tree-structured perfect reconstruction filter bank or any orthonormal filter bank for which no filter length exceeds its decimation factor can be shown as a BOT. We then show that all conventional BOTs map to uniform filter banks. A construction method to design a BOT from any nonuniform filter bank is presented, and finding an optimal tree structure (in the sense of transform coding gain) for a given source is also discussed. The results show that the optimal, nonuniform BOT outperforms uniform BOTs having either the same number of bands or the same size in most cases     

Non-fragile <Emphasis Type="Italic">H</Emphasis><Subscript>2</Subscript> and <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> filter designs for polytopic two-dimensional systems in Roesser model

This paper is concerned with the problem of non-fragile H ₂ and H _∞ filter designs for two-dimensional (2-D) discrete systems in Roesser model with polytopic uncertainties. The filters to be designed are assumed to be with additive norm-bounded coefficient variations which reflect the imprecision in filter implementation. The complicated filter design problem is successfully tackled by using the slack variable technique and imposing a structural restriction on the slack matrix. Explicit expressions of the non-fragile H ₂ and H _∞ filters are given in terms of solutions to a set of linear matrix inequalities (LMIs). An illustrative example is provided to demonstrate the feasibility and effectiveness of the proposed method.     

Impact of forecasting methods on variance ratio in order-up-to level policy

This paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first-order autoregressive process describes the customer demand and an order-up-to inventory policy characterizes the replenishment decision. The impact of exponential smoothing and minimum mean squared error forecasting is measured for both the bullwhip effect and inventory variances. Previous similar studies have focused on investigating the impact of forecasting methods on bullwhip effect. However, little research has been carried out to explore the impact of forecasting methods for both bullwhip effect and inventory variances. Through simulation experiments, it has been found that depending on the structure of the demand process, the appropriate selection of forecasting technique can reduce, or even eliminate (i.e., “dewhip”) the bullwhip effect. However, in terms of inventory variances it has been shown that the inventory variances for the exponential smoothing are greater than the minimum mean squared error forecasting method and that gap increases as lead time increases. These findings will help companies to choose the appropriate forecasting technique depending on the nature of demand. These guidelines can help companies to reduce the bullwhip effect and inventory variances across supply chain.     

On the closeness of the space spanned by the lattice structures for a class of linear phase perfect reconstruction filter banks

The incompleteness of the existing lattice structures has been well established for M-channel FIR linear phase perfect reconstruction filter banks (LPPRFBs) with filter length L>2M in the literature, and even the nonexistence of complete order-one lattice has been reported recently. Thus, a question arises naturally as to how large the space spanned by the existing lattice structure is, and about its closeness over some polynomial transformations. The study for such issue can reveal what sense of optimality the lattice based design for LPPRFBs possesses. Inspired from this perspective, this paper firstly studies the closeness of the space spanned by the existing lattice structures under the polynomial transformations for arbitrary equal-length LPPRFBs. We have shown that this space is closed under the popular polynomial transforms widely used in FB design, which establishes the suboptimality of the lattice based design methods for LPPRFBs. Furthermore, the explicit relationship between the lattice parameters before and after transformations has been shown for describing the closeness of the space spanned by those lattice structures.