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.     

Real-time organic aerosol chemical speciation in the indoor environment using extractive electrospray ionization mass spectrometry

Understanding the sources and composition of organic aerosol (OA) in indoor environments requires rapid measurements, since many emissions and processes have short timescales. However, real-time molecular-level OA measurements have not been reported indoors. Here, we present quantitative measurements, at a time resolution of five seconds, of molecular ions corresponding to diverse aerosol-phase species, by applying extractive electrospray ionization mass spectrometry (EESI-MS) to indoor air analysis for the first time, as part of the highly instrumented HOMEChem field study. We demonstrate how the complex spectra of EESI-MS are screened in order to extract chemical information and investigate the possibility of interference from gas-phase semivolatile species. During experiments that simulated the Thanksgiving US holiday meal preparation, EESI-MS quantified multiple species, including fatty acids, carbohydrates, siloxanes, and phthalates. Intercomparisons with Aerosol Mass Spectrometer (AMS) and Scanning Mobility Particle Sizer suggest that EESI-MS quantified a large fraction of OA. Comparisons with FIGAERO-CIMS shows similar signal levels and good correlation, with a range of 100 for the relative sensitivities. Comparisons with SV-TAG for phthalates and with SV-TAG and AMS for total siloxanes also show strong correlation. EESI-MS observations can be used with gas-phase measurements to identify co-emitted gas- and aerosol-phase species, and this is demonstrated using complementary gas-phase PTR-MS observations.     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

A shell for cooperating expert systems

Abstract: This paper describes a shell for cooperating expert systems that has been developed at the University of Porto. The main goal of this shell is two-fold: to generate a community of cooperative knowledge-based systems and to develop several special reasoning techniques which can be used under a distributed and cooperative paradigm. UPShell is able to convert a set of generated intelligent systems (ISs) into a community of cooperative ISs. In this first version it is already possible to generate different intelligent systems which are able to run 'simultaneously' as separate Unix processes and, using a message-passing mechanism, to communicate among themselves. They can be set to pursue an overall goal in a cooperative way. Moreover, several tasks can be given to each IS to be solved simultaneously, and the IS can switch from task to task according to dynamic priorities reflecting the urgency attached to the specific sub-tasks that emerge. The shell described here may also be used to test, within a distributed environment, some time-bounded reasoning techniques that are presently being developed. The paper has three main parts: a general overview of the UPShell (Section 1); a tutorial explaining, by means of examples, how to use the package (Section 2); and, finally, some considerations on the reasoning techniques used and future improvements (Sections 3–5).     

An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Organic matter release in low temperature thermal treatment of biological sludge for reduction of excess sludge production.

Thermal treatment applied in association with a biological system allows for a significant reduction in excess sludge production (approximately 50%). In general, heat treatment is described as a sludge disintegration technique. This paper offers a thorough study on the impact of heat treatment, at temperatures below 100 degrees C, on the solubilisation of the sludge COD and its biodegradability. Discontinuous heating experiments were performed on activated and digested sludge. At all temperatures tested the released COD for digested sludge was systematically higher than that for activated sludge (15 and 40%, respectively, at 95 degrees C for 40 min of contact time). For the first 30 min, a 1st order kinetic, with respect to the residual COD, was systematically found. In the range of 40-95 degrees C, digested sludge had a lower activation energy than activated sludge (26 kcal/mol compared to 70-160 kcal/mol). COD solubilisation is thus more positively influenced by temperature in the case of activated sludge. This may be due to the significant difference in the ratio of protein/carbohydrate in digested and activated sludge (1-5 and 0.2-0.7, respectively). The increase in the COD/TKN ratio in the solubilised fraction after thermal treatment of activated sludge suggests a preferential solubilisation of proteins over carbohydrates. Respirometric tests performed on the solubilised COD showed that whatever the sludge origin, only 40-50% of released COD is biodegradable at a conventional hydraulic retention time (i.e., 24 h). Hence, heat treatment would act more through organic matter solubilisation rather than by a biodegradability increase.     

Moral value transfer from regulatory fit: What feels right is right and what feels wrong is wrong.

People experience regulatory fit (E. T. Higgins, 2000) when the strategic manner of their goal pursuit suits their regulatory orientation, and this regulatory fit feels right. Fit violation feels wrong. Four studies tested the proposal that experiences of fit can transfer to moral evaluations. The authors examined transfer of feeling wrong from fit violation by having participants in a promotion or prevention focus recall transgressions of commission or omission (Studies 1 and 2). Both studies found that when the type of transgression was a fit violation, participants expressed more guilt. Studies 3 and 4 examined transfer of feeling right from regulatory fit. Participants evaluated conflict resolutions (Study 3) and public policies (Study 4) as more right when the means pursued had fit. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Synthesis,characterization and properties of functionalized styrene–maleimide copolymers

New functionalized styrene–maleimide copolymers were prepared by free radical copolymerization of styrene (St) and N‐4‐carboxybutylmaleimide (NBMI) in chloroform, using 2,2′‐azobisisobutyronitrile (AIBN) as initiator. Monomer and copolymer characterization was carried out by ¹H‐ and ¹³C‐NMR. Copolymer composition was determined by elemental analysis and Fourier‐transform infrared (FTIR) spectroscopy. The glass transition temperature (from DSC) and the thermogravimetric analysis (TGA) of the copolymers were consistent with the thermal behavior and stability observed for alternating St–maleimide copolymers. St–NBMI copolymers crosslinked with divinylbenzene (DVB) were also synthesized and their cation exchange properties evaluated in order to assess the capacity of the new copolymers to bind metallic ions. Copyright © 2005 Society of Chemical Industry