A New Distribution Function for Risk Analysis

This paper presents an alternative to the beta continuous probability distribution for risk analysis. Particular attention has been given to two major applications of distributions, namely project management risk and critical path analysis (PERT). In conjunction with the beta, the triangular and normal distributions are frequently employed in order to give sufficient robustness to risk analysis. The beta distribution, as used in PERT, has a major theoretical implementation flaw. The new distribution was developed to give a possible alternative method of assessing risk. It is shown that the requirement to estimate the most pessimistic variate may be replaced by the probability to exceed the mode. Proposals for other simplifications in risk analysis are discussed. Practical means to validate the most appropriate distributions for risk analysis are outlined, and a cost-data case study is included.     

A warehouse-based design model for reverse logistics

In this paper, an MILP formulation is proposed for the design of a reverse logistics network based on a warehouse location–allocation model, which optimizes, simultaneously, the forward and reverse networks. A single product model with unlimited capacity is first defined. Subsequently, the model is extended to a multi-product capacitated recovery network model, where capacity limitations and a multi-product system can be considered. The proposed model is compared to published work in the field, where different model assumptions have been proposed. Two cases are described so as to gain a better insight into the model and allow a comparative analysis.     

Multicriteria decision making under uncertainty

Formalization for problems of multicriteria decision making under uncertainty is constructed in terms of guaranteed and weak estimates. A relevant definition of the vector maximinimax value is given. Parameterization and approximation of maximum, minimax, and maximinimax values based on the inverse logical convolution are suggested. An application for multicommodity networks is considered. Received: December 13, 2000 / Accepted: August 21, 2001?Published online May 8, 2002     

Quadratic data envelopment analysis

Data Envelopment Analysis (DEA) offers a piece-wise linear approximation of the production frontier. The approximation tends to be poor if the true frontier is not concave, eg in case of economies of scale or of specialisation. To improve the flexibility of the DEA frontier and to gain in empirical fit, we propose to extend DEA towards a more general piece-wise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). We show that QDEA gives statistically consistent estimates for all production frontiers with bounded Hessian eigenvalues. Our Monte-Carlo simulations suggest that QDEA can substantially improve efficiency estimation in finite samples relative to standard DEA models.     

Effective dimensionality approach to the RKKY interaction in multilayer systems

We consider RKKY interaction in a quasi 2D system with nonparabolic dispersion. In our paper we calculate the RKKY range function assuming the in-layer confinement via effective dimensionality approach. We show, that indirect magnetic exchange in our system can be modelled by the effective spectral dimension which equals one.     

Molecular mobility in hydrogels based on poly(acrylic acid) and macrodiisocyanates

Partially water-swellable polymer networks were synthesized on the basis of poly(acrylic acid) and various macrodiisocyanates. Hydrophilic and hydrophobic local regions were revealed in swollen networks (hydrogels) by means of the spin probe technique. The local mobility in hydrophobic regions depends on the macrodiisocyanate structure; however, it is substantially lower than that in hydrophilic regions for all gels. It was assumed that the presence of hydrophobic and hydrophilic regions and the difference in their local dynamics must have a substantial effect on the pharmacokinetics of release of drugs immobilized in these hydrogels.     

Application of rainbow schlieren deflectometry to measure temperature and oxygen concentration in a laminar gas-jet diffusion flame

The quantitative rainbow schlieren deflectometry (RSD) technique was applied to measure temperature and oxygen concentration in an axisymmetric hydrogen gas-jet diffusion flame burning in quiescent air at fuel jet exit Reynolds number of 70. Schlieren measurements were compared with conventional measurements using a thermocouple and a gas-sampling probe. Good agreement between the two measurement techniques was achieved on the fuel-lean side of the flame.     

Flow regime identification in a two-phase flow using wavelet transform

This study addresses the problem of the automatic flow regime identification in two-phase flows in pipes. A novel wavelet transform-based approach is proposed and validated using time series of differential pressure fluctuations. The experimental data on the differential pressure measured in a vertically installed Venturi meter for air-water flow were analyzed and found to be appropriate for flow regime identification. The wavelet spectrum of the measured signal is shown to characterize the flow patterns completely, and the vector of the wavelet variances is proposed as the characteristic vector for use in an on-line flow regime identification system.     

A Recursive Algorithm for Order Cycle-time that Minimizes Logistics Cost

A firm's logistics cost, including shipping and inventory-carrying, is a substantial percentage of its sales. Nevertheless, typical inventory-control methods ignore or insufficiently represent the shipping cost. This paper describes a recursive algorithm that determines the reorder cycle-time that minimizes total logistics cost. It allows for a realistic accounting of shipping cost, which is modelled here as a function of shipping distance and weight. The algorithm uses a relaxation procedure to identify a suitable initial approximation to the optimal order cycle-time and then, through a series of recursive steps, moves to the optimal result. We demonstrate the algorithm with a single item, with a group of items that share a common order cycle, and with multi-items when item demands are random variables. Experience with this algorithm indicates that it converges to the optimal result in a very few steps.