A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

Spin populations in one-dimensional alternant spin systems: A theoretical approach

Spin-density maps, deduced from polarized neutron diffraction experiments, for both the pair and chain compounds of the system Mn2+Cu2+ have been reported recently. These results have motivated us to investigate theoretically the spin populations in such alternant mixed-spin systems. In this paper, we report our studies on the one-dimensional ferrimagnetic systems (S-A,S-B)(N) where hi is the number of AB pairs. We have considered all cases in which the spin Sri takes on allowed values in the range I to 7/2 while the spin S-B is held fixed at 1/2. The theoretical studies have been carried out on the isotropic Heisenberg model, using the density matrix renormalization group method. The effect of the magnitude of the larger spin SA On the quantum fluctuations in both A and B sublattices has been studied as a function of the system size N. We have investigated systems with both periodic and open boundary conditions, the latter with a view to understanding end-of-chain effects. The spin populations have been followed as a function of temperature as well as an applied magnetic field. High-magnetic fields are found to lead to interesting re-entrant behavior. The ratio of spin populations P-A-P-B is not sensitive to temperature at low temperatures.

Synthesis of novel poly[(2,5-dimethoxy-p-phenylene)vinylene] precursors having two eliminatable groups: An approach for the control of conjugation length

Poly[(2,5-dimethoxy-p-phenylene)vinylene] (DMPPV) of varying conjugation length was synthesized by selective elimination of organic soluble precursor polymers that contained two eliminatable groups, namely, methoxy and acetate groups. These precursor copolymers were in turn synthesized by competitive nucleophilic substitution of the sulfonium polyelectrolyte precursor (generated by the standard Wessling route) using methanol and sodium acetate in acetic acid. The composition of the precursor copolymer, in terms of the relative amounts of methoxy and acetate groups, was controlled by varying the composition of the reaction mixture during nucleophilic substitution. Thermal elimination of these precursor copolymers at 250 degrees C, yielded partially conjugated polymers, whose color varied from light yellow to deep red. FT-IR studies confirmed that, while essentially all the acetate groups were eliminated, the methoxy groups were intact and caused the interruption in conjugation. Preliminary photoluminescence studies of the partially eliminated DMPPV samples showed a gradual shift in the emission maximum from 498 to 598 nm with increasing conjugation lengths, suggesting that the color of LED devices fabricated from such polymers can, in principle, be fine-tuned.

Reservoir Operation for Hydropower Optimization: A Chance-Constrained Approach

This paper presents a chance-constrained linear programming formulation for reservoir operation of a multipurpose reservoir. The release policy is defined by a chance constraint that the probability of irrigation release in any period equalling or exceeding the irrigation demand is at least equal to a specified value P (called reliability level). The model determines the maximum annual hydropower produced while meeting the irrigation demand at a specified reliability level. The model considers variation in reservoir water level elevation and also the operating range within which the turbine operates. A linear approximation for nonlinear power production function is assumed and the solution obtained within a specified tolerance limit. The inflow into the reservoir is considered random. The chance constraint is converted into its deterministic equivalent using a linear decision rule and inflow probability distribution. The model application is demonstrated through a case study.

Liquefaction And Pore Water Pressure Generation In Sand - A Cyclic Strain Approach

This paper presents the results of laboratory investigation carried out on Ahmedabad sand on the liquefaction and pore water pressure generation during strain controled cyclic loading. Laboratory experiments were carried out on representative natural sand samples (base sand) collected from earthquake-affected area of Ahmedabad City of Gujarat State in India. A series of strain controled cyclic triaxial tests were carried out on isotropically compressed samples to study the influence of different parameters such as shear strain amplitude, initial effective confining pressure, relative density and percentage of non-plastic fines on the behavior of liquefaction and pore water pressure generation. It has been observed from the laboratory investigation that the potential for liquefaction of the sandy soils depends on the shear strain amplitude, initial relative density, initial effective confining pressure and non-plastic fines. In addition, an empirical relationship between pore pressure ratio and cycle ratio independent of the number of cycles of loading, relative density, confining pressure, amplitude of shear strain and non-plastic fines has been proposed.

Immunochemical approach to the mapping of an assembled epitope of human chorionic gonadotropin: Proximity of CTP-alpha to the receptor binding region of the beta-subunit

A single-step solid-phase RIA (SS-SPRIA) developed in our laboratory using hybridoma culture supernatants has been utilised for the quantitation of epitope-paratope interactions. Using SS-SPRIA as a quantitative tool for the assessment of epitope stability, it was found that several assembled epitopes of human chorionic gonadotropin (hCG) are differentially stable to proteolysis and chemical modification. Based on these observations an approach has been developed for identifying the amino acid residues constituting an epitopic region. This approach has now been used to map an assembled epitope at/near the receptor binding region of the hormone. The mapped site forms a part of the seat belt region and the cystine knot region (C34-C38-C88-C90-H106). The carboxy terminal region of the alpha-subunit forms a part of the epitope indicating its proximity to the receptor binding region. These results are in agreement with the reported receptor binding region identified through other approaches and the X-ray crystal structure of hCG.

Axially Loaded Timoshenko Rotors From A Prestressed Continuum Approach

We consider an axially loaded Timoshenko rotor rotating at a constant speed and derive its governing equations from a continuum viewpoint. The primary aim of this paper is to understand the source and role of gyroscopic terms, when the rotor is viewed not as a Timoshenko beam but as a genuine 3D continuum. We offer the primary insight that macroscopically observed gyroscopic terms may also, quite equivalently, be viewed as external manifestations of internally existing spin-induced prestresses at the continuum level. To demonstrate this idea with an analytical example (the Timoshenko rotor), we have studied the reliable equations of Choi et al. (Journal of Vibration and Acoustics, 114, 1992, 249-259). Using a straightforward application of our insight in the framework of nonlinear elasticity, we obtain equations that exactly match Choi et al. for the case with no axial load. For the case of axial preload, our straightforward formulation leads to a slightly different set of equations that have negligible numerical consequence for solid rotors. However, we offer a macroscopic, intuitive, justification for modifying our formulation so as to obtain the exact equations of Choi et al. with the axial load included.

Enantiospecific approach to the tricyclic core structure of tricycloillicinone, ialibinones, and takaneones via ring-closing metathesis reaction

Enantiospecific synthesis of the tricyclic core structure present in the biologically active natural products tricycloillicinone, ialibinones, and takaneones, starting from the readily available campholenaldehyde employing a transannular RCM reaction as the key step, has been accomplished.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

An eigenproblem approach to classical screw theory

This paper presents a novel algebraic formulation of the central problem of screw theory, namely the determination of the principal screws of a given system. Using the algebra of dual numbers, it shows that the principal screws can be determined via the solution of a generalised eigenproblem of two real, symmetric matrices. This approach allows the study of the principal screws of the general two-, three-systems associated with a manipulator of arbitrary geometry in terms of closed-form expressions of its architecture and configuration parameters. We also present novel methods for the determination of the principal screws for four-, five-systems which do not require the explicit computation of the reciprocal systems. Principal screws of the systems of different orders are identified from one uniform criterion, namely that the pitches of the principal screws are the extreme values of the pitch.The classical results of screw theory, namely the equations for the cylindroid and the pitch-hyperboloid associated with the two-and three-systems, respectively have been derived within the proposed framework. Algebraic conditions have been derived for some of the special screw systems. The formulation is also illustrated with several examples including two spatial manipulators of serial and parallel architecture, respectively.

2.5-dimensional solution of the advective accretion disk:a self-similar approach

We provide a 2.5-dimensional solution to a complete set of viscous hydrodynamical equations describing accretion- induced outflows and plausible jets around black holes/compact objects. We prescribe a self-consistent advective disk-outflow coupling model, which explicitly includes the information of vertical flux. Inter-connecting dynamics of an inflow-outflow system essentially upholds the conservation laws. We provide a set of analytical family of solutions through a self-similar approach. The flow parameters of the disk-outflow system depend strongly on the viscosity parameter α and the cooling factor.

A pseudo-dynamical systems approach to a class of inverse problems in engineering

A pseudo-dynamical approach for a class of inverse problems involving static measurements is proposed and explored. Following linearization of the minimizing functional associated with the underlying optimization problem, the new strategy results in a system of linearized ordinary differential equations (ODEs) whose steady-state solutions yield the desired reconstruction. We consider some explicit and implicit schemes for integrating the ODEs and thus establish a deterministic reconstruction strategy without an explicit use of regularization. A stochastic reconstruction strategy is then developed making use of an ensemble Kalman filter wherein these ODEs serve as the measurement model. Finally, we assess the numerical efficacy of the developed tools against a few linear and nonlinear inverse problems of engineering interest.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Thermal reactivity of poly(styrene peroxide): a thermodynamic approach

Abstract is not available.