Metaheuristics for the Order Batching Problem in Manual Order Picking Systems

In manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations effciently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem; the rst one is based on Iterated Local Search, the second one on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods, but provide solutions which may allow for operating distribution warehouses signicantly more effcient.Warehouse Management, Order Picking, Order Batching, Iterated Local Search, Ant Colony Optimization

Metaheuristics for the Order Batching Problem in Manual Order Picking Systems

In manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations effciently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem; the rst one is based on Iterated Local Search, the second one on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods, but provide solutions which may allow for operating distribution warehouses signi cantly more effcient

The Seasonal Fluctuation of Fatigue in Multiple Sclerosis.

Background Fatigue is a common symptom in patients with multiple sclerosis. Several studies suggest that outdoor temperature can impact fatigue severity, but a systematic study of seasonal variations is lacking. Methods Fatigue was assessed with the Fatigue Scale for Motor and Cognitive Functions (FSMC) in a temperate climatic zone with an average outdoor temperature of 8.8°C. This study included 258 patients with multiple sclerosis from 572 visits temporally distributed over the year. The data were adjusted for age, sex, cognition, depression, disease severity, and follow-up time. Linear regression models were performed to determine whether the temporal course of fatigue was time-independent, linearly time dependent, or non-linearly time dependent. Results Fatigue was lowest during January (mean FSMC: 49.84) and highest during August (mean FSMC: 53.88). The regression analysis showed the best fit with a model that included months + months2, which was a non-linear time dependency. Mean FSMC per month correlated significantly with the average monthly temperature (ρ = 0.972; p < 0.001). Conclusion In multiple sclerosis, fatigue showed a natural temporal fluctuation. Fatigue was higher during summer compared to winter, with a significant relationship of fatigue with outdoor temperature. This finding should be carefully taken into account when clinically monitoring patients over time to not interpret higher or lower scores independent of seasonal aspects

The genesis of Yedoma Ice Complex permafrost – grain-size endmember modeling analysis from Siberia and Alaska

The late Pleistocene Yedoma Ice Complex is an ice-rich and organic-bearing type of permafrost deposit widely distributed across Beringia and is assumed to be especially prone to deep degradation with warming temperature, which is a potential tipping point of the climate system. To better understand Yedoma formation, its local characteristics, and its regional sedimentological composition, we compiled the grain-size distributions (GSDs) of 771 samples from 23 Yedoma locations across the Arctic; samples from sites located close together were pooled to form 17 study sites. In addition, we studied 160 samples from three non-Yedoma ice-wedge polygon and floodplain sites for the comparison of Yedoma samples with Holocene depositional environments. The multimodal GSDs indicate that a variety of sediment production, transport, and depositional processes were involved in Yedoma formation. To disentangle these processes, a robust endmember modeling analysis (rEMMA) was performed. Nine robust grain-size endmembers (rEMs) characterize Yedoma deposits across Beringia. The study sites of Yedoma deposits were finally classified using cluster analysis. The resulting four clusters consisted of two to five sites that are distributed randomly across northeastern Siberia and Alaska, suggesting that the differences are associated with rather local conditions. In contrast to prior studies suggesting a largely aeolian contribution to Yedoma sedimentation, the wide range of rEMs indicates that aeolian sedimentation processes cannot explain the entire variability found in GSDs of Yedoma deposits. Instead, Yedoma sedimentation is controlled by local conditions such as source rocks and weathering processes, nearby paleotopography, and diverse sediment transport processes. Our findings support the hypothesis of a polygenetic Yedoma origin involving alluvial, fluvial, and niveo-aeolian transport; accumulation in ponding waters; and in situ frost weathering as well as postdepositional processes of solifluction, cryoturbation, and pedogenesis. The characteristic rEM composition of the Yedoma clusters will help to improve how grain-size-dependent parameters in permafrost models and soil carbon budgets are considered. Our results show the characteristic properties of ice-rich Yedoma deposits in the terrestrial Arctic. Characterizing and quantifying site-specific past depositional processes is crucial for elucidating and understanding the trajectories of this unique kind of ice-rich permafrost in a warmer future

Microbial lipid signatures and substrate potential of organic matter in permafrost deposits - implications for future greenhouse gas production

A terrestrial permafrost core from Buor Khaya in northern Siberia comprising deposits of Late Pleistocene to Early Holocene age has been investigated to characterize living and past microbial communities with respect to modern and paleoclimate environmental conditions, and to evaluate the potential of the organic matter (OM) for greenhouse gas generation. Microbial life markers - intact phospholipids and phospholipid fatty acids - are found throughout the entire core and indicate the presence of living microorganisms also in older permafrost deposits. Biomarkers for past microbial communities (branched and isoprenoid GDGT as well as archaeol) reveal links between increased past microbial activity and intervals of high OM accumulation accompanied by increased OM quality presumably caused by local periods of moister and warmer environmental conditions. Concentrations of acetate as an excellent substrate for methanogenesis are used to assess the OM quality with respect to microbial degradability for greenhouse gas production. For this purpose two acetate pools are determined: the pore-water acetate and OM bound acetate. Both depth profiles reveal similarities to the OM content and quality indicating a link between the amount of the stored OM and the potential to provide substrates for microbial greenhouse gas production. The data suggest that OM stored in the permafrost deposits is not much different in terms of OM quality than the fresh surface organic material. Considering the expected increase of permafrost thaw due to climate warming, this implies a potentially strong impact on greenhouse gas generation from permafrost areas in future with positive feedback on climate variation

A Survey of z ~ 6 Quasars in the Sloan Digital Sky Survey Deep Stripe. II. Discovery of Six Quasars at z AB>21

We present the discovery of six new quasars at z ~ 6 selected from the Sloan Digital Sky Survey (SDSS) southern survey, a deep imaging survey obtained by repeatedly scanning a stripe along the celestial equator. The six quasars are about 2 mag fainter than the luminous z ~ 6 quasars found in the SDSS main survey and 1 mag fainter than the quasars reported in Paper I. Four of them comprise a complete flux-limited sample at 21 < z_(AB) < 21.8 over an effective area of 195 deg^2. The other two quasars are fainter than z_(AB) = 22 and are not part of the complete sample. The quasar luminosity function at z ~ 6 is well described as a single power law Φ(L_(1450))α L^β_(1450) over the luminosity range –28 < M_(1450) < –25. The best-fitting slope β varies from –2.6 to –3.1, depending on the quasar samples used, with a statistical error of 0.3-0.4. About 40% of the quasars discovered in the SDSS southern survey have very narrow Lyα emission lines, which may indicate small black hole masses and high Eddington luminosity ratios, and therefore short black hole growth timescales for these faint quasars at early epochs

Dust Reddening in SDSS Quasars

We explore the form of extragalactic reddening toward quasars using a sample of 9566 quasars with redshifts 0<z<2.2, and accurate optical colors from the Sloan Digital Sky Survey (SDSS). We confirm that dust reddening is the primary explanation for the red ``tail'' of the color distribution of SDSS quasars. Our fitting to 5-band photometry normalized by the modal quasar color as a function of redshift shows that this ``tail'' is well described by SMC-like reddening but not by LMC-like, Galactic, or Gaskell et al. (2004) reddening. Extension to longer wavelengths using a subset of 1886 SDSS-2MASS matches confirms these results at high significance. We carry out Monte-Carlo simulations that match the observed distribution of quasar spectral energy distributions using a Lorentzian dust reddening distribution; 2% of quasars selected by the main SDSS targeting algorithm (i.e., which are not extincted out of the sample) have E_{B-V} > 0.1; less than 1% have E_{B-V} > 0.2, where the extinction is relative to quasars with modal colors. Reddening is uncorrelated with the presence of intervening narrow-line absorption systems, but reddened quasars are much more likely to show narrow absorption at the redshift of the quasar than are unreddened quasars. Thus the reddening towards quasars is dominated by SMC-like dust at the quasar redshift.Comment: 29 pages including 8 figures. AJ, September 2004 issu

Non-thermal effects of radiofrequency electromagnetic fields

We explored the non-thermal effects of radiofrequency (RF) electromagnetic fields and established a theoretical framework to elucidate their electrophysiological mechanisms. In experiments, we used a preclinical treatment device to treat the human colon cancer cell lines HT-29 and SW480 with either water bath heating (WB-HT) or 13.56 MHz RF hyperthermia (RF-HT) at 42 degrees C for 60 min and analyzed the proliferation and clonogenicity. We elaborated an electrical model for cell membranes and ion channels and estimated the resulting ion fluxes. The results showed that, for both cell lines, using RF-HT significantly reduced proliferation and clonogenicity compared to WB-HT. According to our model, the RF electric field component was rectified and smoothed in the direction of the channel, which resulted in a DC voltage of similar to 1 mu V. This may induce ion fluxes that can potentially cause relevant disequilibrium of most ions. Therefore, RF-HT creates additional non-thermal effects in association with significant ion fluxes. Increasing the understanding of these effects can help improve cancer therapy

A review of revenue management : recent generalizations and advances in industry applications

Originating from passenger air transport, revenue management has evolved into a general and indispensable methodological framework over the last decades, comprising techniques to manage demand actively and to further improve companies’ profits in many different industries. This article is the second and final part of a paper series surveying the scientific developments and achievements in revenue management over the past 15 years. The first part focused on the general methodological advances regarding choice-based theory and methods of availability control over time. In this second part, we discuss some of the most important generalizations of the standard revenue management setting: product innovations (opaque products and flexible products), upgrading, overbooking, personalization, and risk-aversion. Furthermore, to demonstrate the broad use of revenue management, we survey important industry applications beyond passenger air transportation that have received scientific attention over the years, covering air cargo, hotel, car rental, attended home delivery, and manufacturing. We work out the specific revenue management-related challenges of each industry and portray the key contributions from the literature. We conclude the paper with some directions for future research