28 research outputs found
Stochastic Improvement of Cyclic Railway Timetables
Real-time railway operations are subject to stochastic disturbances. However, a railway timetable is a deterministic plan. Thus a timetable should be designed in such a way that it can cope with the stochastic disturbances as well as possible. For that purpose, a timetable usually contains time supplements in several process times and buffer times between pairs of consecutive trains. This paper describes a Stochastic Optimization Model that can be used to allocate the time supplements and the buffer times in a given timetable in such a way that the timetable becomes maximally robust against stochastic disturbances. The Stochastic Optimization Model was tested on several instances of NS Reizigers, the main operator of passenger trains in the Netherlands. Moreover, a timetable that was computed by the model was operated in practice in a timetable experiment on the so-called “Zaanlijnâ€. The results show that the average delays of trains can often be reduced significantly by applying relatively small modifications to a given timetable.Railway Timetabling;Stochastic Optimization;Robustness
Green Lot-Sizing
The lot-sizing problem concerns a manufacturer that needs to solve a production planning problem. The producer must decide at which points in time to set up a production process, and when he/she does, how much to produce. There is a trade-off bet
Economic lot-sizing with remanufacturing: complexity and efficient formulations
Within the framework of reverse logistics, the classic economic lot-sizing problem has been extended with a remanufacturing option. In this extended problem, known quantities of used products are returned from customers in each period. These returned products can be remanufactured, so that they are as good as new. Customer demand can then be fulfilled both from newly produced and remanufactured items. In each period, we can choose to set up a process to remanufacture returned products or produce new items. These processes can have separate or joint set-up costs. In this paper, we show that both variants are NP-hard. Furthermore, we propose and compare several alternative MIP formulations of both problems. Because ‘natural’ lot-sizing formulations provide weak lower bounds, we propose tighter formulations, namely shortest path formulations, a partial shortest path formulation and an adaptation of the (l, S, WW)-inequalities for the classic problem with Wagner-Whitin costs. We test their efficiency on a large number of test data sets and find that, for both problem variants, a (partial) shortest path type formulation performs better than the natural formulation, in terms of both the LP relaxation and MIP computation times. Moreover, this improvement can be substantial
The Economic Lot-Sizing Problem with an Emission Constraint
We consider a generalisation of the lot-sizing problem that includes an emission constraint. Besides the usual financial costs, there are emissions associated with production, keeping inventory and setting up the production process. Because the constraint on the emissions can be seen as a constraint on an alternative cost function, there is also a clear link with bi-objective optimisation. We show that lot-sizing with an emission constraint is NP-hard and propose several solution methods. First, we present a Lagrangian heuristic to provide a feasible solution and lower bound for the problem. For costs and emissions for which the zero inventory property is satisfied, we give a pseudo-polynomial algorithm, which can also be used to identify the complete Pareto frontier of the bi-objectiv
Stochastic Improvement of Cyclic Railway Timetables
Real-time railway operations are subject to stochastic disturbances. However, a railway timetable is a deterministic plan. Thus a timetable should be designed in such a way that it can cope with the stochastic disturbances as well as possible. For that purpose, a timetable usually contains time supplements in several process times and buffer times between pairs of consecutive trains. This paper describes a Stochastic Optimization Model that can be used to allocate the time supplements and the buffer times in a given timetable in such a way that the timetable becomes maximally robust against stochastic disturbances. The Stochastic Optimization Model was tested on several instances of NS Reizigers, the main operator of passenger trains in the Netherlands. Moreover, a timetable that was computed by the model was operated in practice in a timetable experiment on the so-called “Zaanlijn”. The results show that the average delays of trains can often be reduced significantly by applying relatively small modifications to a given timetable
A decomposition algorithm for robust lot sizing problem with remanufacturing option
In this paper, we propose a decomposition procedure for constructing robust optimal production plans for reverse inventory systems. Our method is motivated by the need of overcoming the excessive computational time requirements, as well as the inaccuracies caused by imprecise representations of problem parameters. The method is based on a min-max formulation that avoids the excessive conservatism of the dualization technique employed by Wei et al. (2011). We perform a computational study using our decomposition framework on several classes of computer generated test instances and we report our experience. Bienstock and Özbay (2008) computed optimal base stock levels for the traditional lot sizing problem when the production cost is linear and we extend this work here by considering return inventories and setup costs for production. We use the approach of Bertsimas and Sim (2004) to model the uncertainties in the input
Serum metabolome associated with severity of acute traumatic brain injury
Traumatic brain injury is associated with changes to the metabolome. Here the authors show that acute traumatic brain injury has distinctive serum metabolic patterns which may suggest protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.</p
Serum metabolome associated with severity of acute traumatic brain injury
Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain
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Occurrence and timing of withdrawal of life-sustaining measures in traumatic brain injury patients: a CENTER-TBI study
Funder: National Institute for Health Research (UK)Abstract: Background: In patients with severe brain injury, withdrawal of life-sustaining measures (WLSM) is common in intensive care units (ICU). WLSM constitutes a dilemma: instituting WLSM too early could result in death despite the possibility of an acceptable functional outcome, whereas delaying WLSM could unnecessarily burden patients, families, clinicians, and hospital resources. We aimed to describe the occurrence and timing of WLSM, and factors associated with timing of WLSM in European ICUs in patients with traumatic brain injury (TBI). Methods: The CENTER-TBI Study is a prospective multi-center cohort study. For the current study, patients with traumatic brain injury (TBI) admitted to the ICU and aged 16 or older were included. Occurrence and timing of WLSM were documented. For the analyses, we dichotomized timing of WLSM in early (< 72 h after injury) versus later (≥ 72 h after injury) based on recent guideline recommendations. We assessed factors associated with initiating WLSM early versus later, including geographic region, center, patient, injury, and treatment characteristics with univariable and multivariable (mixed effects) logistic regression. Results: A total of 2022 patients aged 16 or older were admitted to the ICU. ICU mortality was 13% (n = 267). Of these, 229 (86%) patients died after WLSM, and were included in the analyses. The occurrence of WLSM varied between regions ranging from 0% in Eastern Europe to 96% in Northern Europe. In 51% of the patients, WLSM was early. Patients in the early WLSM group had a lower maximum therapy intensity level (TIL) score than patients in the later WLSM group (median of 5 versus 10) The strongest independent variables associated with early WLSM were one unreactive pupil (odds ratio (OR) 4.0, 95% confidence interval (CI) 1.3–12.4) or two unreactive pupils (OR 5.8, CI 2.6–13.1) compared to two reactive pupils, and an Injury Severity Score (ISS) if over 41 (OR per point above 41 = 1.1, CI 1.0–1.1). Timing of WLSM was not significantly associated with region or center. Conclusion: WLSM occurs early in half of the patients, mostly in patients with severe TBI affecting brainstem reflexes who were severely injured. We found no regional or center influences in timing of WLSM. Whether WLSM is always appropriate or may contribute to a self-fulfilling prophecy requires further research and argues for reluctance to institute WLSM early in case of any doubt on prognosis