The relationship between highly-cited papers and the frequency of citations to other papers within-issue among three top information science journals

Scientometrics - This study investigates a potential relationship between highly-cited scholarly papers and the number of citations received by other papers with which they share a journal issue....     

Steels for Bridge Structures

Metallurgist - We consider domestic and foreign standards for rolled metals used in bridge building. Domestic standards contain elevated requirements to the reliability of rolled metals in terms of...     

Investigation into the Influence of Sodium Lignosulfonate,Anionic Surfactants,and Their Mixtures on the Copper Cementation Rate by Zinc

Russian Journal of Non-Ferrous Metals - This article is devoted to the influence of sodium lignosulfonate (SL), anionic surfactants (sodium dodecylsulfate (SDS), sodium dodecylbenzene sulfonate...     

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.