Job shop scheduling(JSS) is a hard problem with most of the research focused on scenarios with the assumption that the shop parameters such as processing times, due dates are constant. But in the real world uncertainty in such parameters is a major issue. In this work, we investigate a genetic programming based hyper-heuristic approach to evolving dispatching rules suitable for dynamic job shop...

The standard probability tree methodology of probabilistic seismic hazard assessment (PSHA) allows for the explicit treatment of many kinds of uncertainty. These include both epistemic uncertainty (e.g., uncertainty in the parameters of the frequency-magnitude relation for a given source region, and in the form and parameters of relations for attenuation of strong shaking) and aleatory uncertai...

There is confusion in the medical decision-making literature about how to handle uncertainty in medical tests. In this article, the authors consider the situation in which there is uncertainty about the pretest probability of a disease in a patient as well as uncertainty about the sensitivity and specificity of a diagnostic test for that disease. They discuss how to calculate posttest probabili...

• Best-Estimate-Plus-Uncertainty analysis of SPERT-III RIA experiments. Nuclear Data uncertainty propagation in CASMO down to SIMULATE-3K. Identify dominant nuclear data contributors overall uncertainty. Impact cross-section perturbation the resonance self-shielding calculation. kinetic parameters’ uncertainties. The current research summarizes recent developments performed within PSI BEPU meth...

in this paper, we consider a multi-site production planning problem subject to uncertainty in demand and workforce expenses. in our new mathematical model, we presented a production planning system considering failure in rework and breakdown. we also survey human workforce allocation and its expenses which are considered uncertain due to some tradeoff between company’s benefits and workforce :u...

Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...

BACKGROUND Aedes aegypti is one of the most important mosquito vectors of human disease. The development of spatial models for Ae. aegypti provides a promising start toward model-guided vector control and risk assessment, but this will only be possible if models make reliable predictions. The reliability of model predictions is affected by specific sources of uncertainty in the model. METHODO...

Quantification of the uncertainty in constitutive model predictions describing arterial wall mechanics is vital towards non-invasive assessment of vascular drug therapies. Therefore, we perform uncertainty quantification to determine uncertainty in mechanical characteristics describing the vessel wall response upon loading. Furthermore, a global variance-based sensitivity analysis is performed ...

It is important to determine the soil–water characteristic curve (SWCC) for analyzing slope seepage and stability under the conditions of rainfall. However, SWCCs exhibit high uncertainty because of complex influencing factors, which has not been previously considered in slope seepage and stability analysis under conditions of rainfall. This study aimed to evaluate the uncertainty of the SWCC a...

Since the Guide to the Expression of Uncertainty in Measurement (GUM) was published in 1993 it has changed the evaluation of physical and chemical measurements. Nowadays almost all high level measurements include a detailed evaluation of uncertainty. This allows the scientific community to do the next step and evaluate uncertainty for derived evaluations like parameter fittings. The evaluation ...