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.     

Luminescent Eu(III) hybrid sensors for in situ copper detection

In this work we used the sol-gel technique to develop luminescent Eu(III) transparent films deposited on glass slides to build for sensor devices capable of monitoring transition metal ions in aqueous solutions. The films were obtained from a bis(trialkoxysilyl) organic precursor synthesized from the amide of the 2,6-pyridinedicarboxylic acid (DPA) with aminopropyltriethoxysilane (APTES) in the presence or absence of cetyl trimethyl ammonium bromide (CTAB) surfactant as templating agent and triethylethoxysilane (TEOS) as crosslinker. These sensor devices were used to perform in situ quenching experiments by Cu(II), Fe(III), Co(II) and Ni(II) ions. The results indicate that the templated films allow the detection and quantification of these metals down to ppb levels by means of the values of the Stern-Volmer constants. In particular, it was shown that Cu(II) acts as an extremely efficient quencher (K_SV = 3.5 × 10⁵ M⁻¹) when compared with the results obtained for the other metals, opening the possibility to use these devices as potential Cu(II) sensors for actual applications in aqueous media.     

Production of Methyl Oleate in Reactive‐Separation Systems

The esterification of oleic acid and methanol using sulfuric acid as a homogeneous catalyst is studied in reactive‐separation systems. The conversion of the free fatty acid was investigated in two different experiments with the molar ratio of methanol/oleic acid, amount of catalyst, temperature, and reaction time as variables. The conversion of the free fatty acid was found to depend strongly on the molar ratio of methanol/oleic acid. The reaction time had a direct effect on the conversion of the free fatty acid, and this conversion decreased with higher temperature. These results were valuable for a preliminary study on biodiesel production, using an acid homogeneous catalyst in a reactive dividing‐wall distillation column.     

Addendum to “On the consistency of MPS” [Comput. Phys. Comm. 184 (3) (2013) 732–745]

The analogies between the Moving Particle Semi-implicit method (MPS) and Incompressible Smoothed Particle Hydrodynamics method (ISPH) are established in this note, as an extension of the MPS consistency analysis conducted in Souto-Iglesias et al. (2013).     

Analysis of polyolefin compositions through near infrared spectroscopy

In this work, NIRS is employed to provide compositions of α‐olefin copolymers, allowing for evaluation of the effects of certain key process variables on the final NIR spectral responses of obtained polymer materials. This work also introduces a new temperature programmed analytical technique, which combines NIRS measurements with partial fractionation of α‐olefin copolymers. The new proposed technique can be used for evaluation of polyolefin compositions, as presented here for poly(propene/1‐butene) copolymers. Besides, preliminary results obtained from thermal fractionation experiments indicate that this new proposed experimental technique can be employed for characterization of comonomer sequence distributions of α‐olefin copolymers. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40127.     

Caloric beverage consumption patterns in Mexican children

Background  

Mexico has seen a very steep increase in child obesity level. Little is known about caloric beverage intake in this country as well as all other countries outside a few high income countries. This study examines overall patterns and trends in all caloric beverages from two nationally representative surveys from Mexico.     

Smooth sliding-mode observers for specific growth rate and substrate from biomass measurement

This paper addresses the estimation of specific growth rate and substrate concentration from biomass measurements in fermentation processes. Specifically, sliding-mode observers are proposed, for which finite-time global convergence is demonstrated using Lyapunov stability theory and concepts of variable structure systems. Two observers are developed for specific growth rate estimation, one producing a discontinuous estimation which is used afterwards for substrate estimation, and the other one – based on high-gain observers – that generates a smooth estimation with first-order dynamics and finite-time bounded convergence error. In the case of substrate estimation, an observer that increases the convergence rate to a vicinity of the real substrate concentration while achieving asymptotic convergence despite kinetic model uncertainties in properly excited processes is designed. This observer also exhibits first-order dynamics.     

Artificial neural networks for machining processes surface roughness modeling

In recent years, several papers on machining processes have focused on the use of artificial neural networks for modeling surface roughness. Even in such a specific niche of engineering literature, the papers differ considerably in terms of how they define network architectures and validate results, as well as in their training algorithms, error measures, and the like. Furthermore, a perusal of the individual papers leaves a researcher without a clear, sweeping view of what the field’s cutting edge is. Hence, this work reviews a number of these papers, providing a summary and analysis of the findings. Based on recommendations made by scholars of neurocomputing and statistics, the review includes a set of comparison criteria as well as assesses how the research findings were validated. This work also identifies trends in the literature and highlights their main differences. Ultimately, this work points to underexplored issues for future research and shows ways to improve how the results are validated.     

Integrated sliding-mode algorithms in robot tracking applications

An integrated solution based on sliding mode ideas is proposed for robotic trajectory tracking. The proposal includes three sliding-mode algorithms for speed auto-regulation, path conditioning and redundancy resolution in order to fulfill velocity, workspace and C-space constraints, respectively. The proposed method only requires a few program lines and simplifies the robot user interface since it directly deals with the fulfillment of the constraints to find a feasible solution for the robot trajectory tracking in a short computation time. The proposed approach is evaluated in simulation on the freely accessible 6R robot model PUMA-560, for which the main features of the method are illustrated.     

A Novel Calibration Algorithm for a Special Class of Multiport Vector Network Analyzers

A new error model for a special class of multiport vector network analyzers (VNAs) is presented in this paper. This model can be applied to multiport network analyzers with noncomplete reflectometers, i.e., when the measurement of the incident waves at each port is not always available. The method used to compute the error coefficients proposed here is based on a compact and easy formulation. This method is an extension of the already existing general theory for complete reflectometer multiport network analyzers. Furthermore, the new error model generalizes the theory for three-sampler two-port VNAs. The proposed model has been tested against the complete reflectometer one and exhibits the same accuracy level.