From stochastic dominance to mean-risk models: Semideviations as risk measures

Two methods are frequently used for modeling the choice among uncertain outcomes: stochastic dominance and mean-risk approaches. The former is based on an axiomatic model of risk-averse preferences but does not provide a convenient computational recipe. The latter quantifies the problem in a lucid form of two criteria with possible trade-off analysis, but cannot model all risk-averse preferences. In particular, if variance is used as a measure of risk, the resulting mean–variance (Markowitz) model is, in general, not consistent with stochastic dominance rules. This paper shows that the standard semideviation (square root of the semivariance) as the risk measure makes the mean-risk model consistent with the second degree stochastic dominance, provided that the trade-off coefficient is bounded by a certain constant. Similar results are obtained for the absolute semideviation, and for the absolute and standard deviations in the case of symmetric or bounded distributions. In the analysis we use a new tool, the Outcome–Risk (O–R) diagram, which appears to be particularly useful for comparing uncertain outcomes.     

Probabilistic judgments specified partially in the analytic hierarchy process

The Analytic Hierarchy Process (AHP) is a decision-making tool which yields priorities for decision alternatives. This paper proposes a new approach to elicit and synthesize expert assessments for the group decision process in the AHP. These new elicitations are given as partial probabilistic specifications of the entries of pairwise comparisons matrices. For a particular entry of the matrix, the partial probabilistic elicitations could arise in the form of either probability assignments regarding the chance of that entry falling in specified intervals or selected quantiles for that entry. A new class of models is introduced to provide methods for processing this partial probabilistic information. One advantage of this approach is that it allows to generate as many pairwise comparison matrices of the decision alternatives as one desires. This, in turn, allows us to determine the statistical significance of the priorities of decision alternatives.     

Optimal joint pricing and lot sizing with fixed and variable capacity

This paper examines previously unexplored fixed and variable capacity problems of jointly determining an item's price and lot size for a profit-maximizing firm facing constant but price-dependent demands over a planning horizon. We apply geometric programming to these constrained nonlinear maximization problems with nonconcave objective functions and obtain global optimal solutions. Using Kuhn-Tucker condition, marginal and sensitivity analyses, we investigate model interactions, provide managerial implications on the optimal capacity decisions, and explore the postoptimal behavior of the price, lot size, and capacity expansion and reduction size. Some findings cast interesting insights, different from previous just-in-time management studies without pricing consideration.     

Impulsive synchronization of Lorenz systems

We study impulsive synchronization of two Lorenz systems. In an impulsive synchronization scheme, driving signals are transmitted to the driven system at discrete instants. The driven system changes its state variables instantaneously at these discrete instants according to synchronization errors. An asymptotically stable impulsive synchronization scheme is presented. The boundaries of stable regions of impulsive synchronization are also presented. Computer simulation results are given.     

Formulating dynamic strategies using decision calculus

This paper presents an applied methodology to assist managers in strategically setting prices and allocating resources over the product, brand, or adoption (diffusion) life cycle. While substantial theoretical work has been achieved in this area in the management science and operations research disciplines, approaches which can be implemented as managerial tools are generally lacking. Our methodology, which has been applied as a PC-based decision support tool in the telecommunications industry, marries the dynamic optimization literature with decision calculus approaches offering sufficient flexibility for applied contexts. We discuss the approach and describe its use to derive optimal price and advertising policies. Strategies not commonly suggested using traditional formulations are also presented.     

Time and temperature dependent correlation functions of 1D models of quantum statistical mechanics

We consider exactly solvable, gapless models of statistical mechanics. We found the universal formula which describes the asymptotics of correlation functions at any temperature and an arbitrary coupling constant.     

Tracking unstable fixed points in parametrically dynamic systems

The method of Ott, Grebogi and Yorke is extended to control a two-parameter system when one of the parameters is time dependent and the other is used as the control-parameter. As one of the parameters changes, the unstable fixed point follows its branch of the bifurcation tree. We control a chaotic orbit such that it tracks this “moving” unstable fixed point using an adaptive control method.     

Vacancy defect influences on optoelectronic properties for In0.875Ga0.125As0.25P0.75: a first-principles study

Optical Review - InGaAsP photocathodes show great potential for near-infrared applications, particularly at 1.06 μm. However, vacancy defects are unavoidable in InGaAsP crystals...     

The information value of logistics platforms in a freight matching market

The information asymmetry in the freight matching of the long-haul trucking industry usually pushes shippers to join a logistics platform that has better knowledge of truckers’ cost information. A logistics platform that is plugged into a freight transportation system helps shippers overcome their information disadvantage but produces the double marginalization effect. We investigate the equilibrium characteristics of a shipper and logistics platform in the freight matching market and find that the shipper prefers to cooperate with the logistics platform in a small-scale sales market but searches for truckers by himself in a large-scale sales market. We show that the information value of a logistics platform for the freight system consists of two aspects: (i) employ low-cost truckers for the shipper and avoid the shipper’s inefficient expansion of the selling quantity in a moderate-scale sales market with greatly heterogeneous truckers, and (ii) improve both the total profit and social welfare of the freight system in a small-scale sales market. We further find that the shipper’s private information may hurt the logistics platform and the logistics platform can mitigate her double marginalization disadvantage by improving value-added services or lowering the logistics price in a large-scale market. Our findings provide guidelines for the shipper and logistics platform on how to choose the appropriate transportation strategy and employment strategy in different logistics markets.