A practical assessment of risk-averse approaches in production lot-sizing problems

ABSTRACT

This paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.     

Design and Optimization of Thick-Walled Cylinders with Load Localization Near the End Face

Strength of Materials - The paper presents a procedure for determining the design parameters of multilayer thick-walled structures with a local load on the inner surface portion located near the...     

Cerebral microbleeds and cognitive decline in a hemodialysis patient: Case report and review of literature

Cerebral microbleeds (CMBs) are small hemosiderin deposits indicative of prior cerebral microscopic hemorrhage and previously thought to be clinically silent. Recent population‐based cross‐sectional studies and prospective longitudinal cohort studies have revealed association between CMB and cognitive dysfunction. In the general population, CMBs are associated with age, hypertension, and cerebral amyloid angiopathy. In the chronic kidney disease (CKD) population, diminished estimated glomerular filtration rate has been found to be an independent risk factor for CMB, raising the possibility that a uremic milieu may predispose to microbleeds. In the end‐stage renal disease (ESRD) population on hemodialysis, the incidence of microbleeds is significantly higher compared with a control group without history of CKD or stroke. We present an ESRD patient on chronic hemodialysis with a history of gradual cognitive decline and progressive CMBs. Through this case and literature review, we illustrate the need to develop detection and prediction models to treat this frequent development in ESRD patients.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Lipase‐catalyzed synthesis of aliphatic poly(β‐thioether ester) with various methylene group contents: thermal properties,crystallization and degradation

A series of novel aliphatic poly(β‐thioether ester)s with various methylene group contents were prepared by direct lipase‐catalyzed polycondensation of the monomer with an acid‐labile β‐thiopropionate group. The polycondensation reaction using immobilized lipase B from Candida antarctica was carried out in diphenyl ether at 90 °C. Poly(β‐thioether ester)s with high molecular weights of 20 500–57 000 Da and narrow polydispersities in the range 1.40–1.48 were obtained. Thermogravimetric analysis, differential scanning calorimetry and wide‐angle X‐ray diffraction were used to investigate the thermal properties and crystal structures of these polyesters. All the poly(β‐thioether ester)s were semicrystalline polymers and thermally stable up to at least 200 °C. In vitro degradation studies showed that they can rapidly degrade under acidic conditions by the hydrolysis of the β‐thiopropionate groups, suggesting their potential as acid‐degradable polymeric materials. © 2019 Society of Chemical Industry     

Effect of hyperbranched poly(citric polyethylene glycol) with various polyethylene glycol chain lengths on starch plasticization and retrogradation

A series of hyperbranched poly(citric polyethylene glycol) (PCPEG) materials with varied polyethylene glycol (PEG) chain lengths as plasticizers were mixed with maize starch (MS) via cooking and film‐forming. The structure, pasting property, plasticization, aging property, moisture absorption and compatibility of plasticized starches were studied by means of Fourier transform infrared spectroscopy, X‐ray diffraction, rapid viscosity analysis, tension testing, moisture absorption measurements and scanning electron microscopy. Compared with PEG and citric acid, PCPEG was more effective in promoting starch chain movement and inhibiting the retrogradation of starch film. Also, PCPEG/MS had smaller moisture content. The longer the plasticizer chain, the better were the aging resistance and moisture resistance of starch. But with an increase of PEG chain length, mechanical properties of PCPEG/MS deteriorated and the compatibility between PCPEG and MS decreased. The hyperbranched derivative of PEG with longer chain exhibited improved plasticization and compatibility with starch. © 2019 Society of Chemical Industry