3 research outputs found
An Improved Robust Optimization Approach for Scheduling Under Uncertainty
In practice, the uncertainty in processing time data frequently affects the feasibility of
optimal solution of the nominal production scheduling problem. Using the unit-specific
event-based continuous time model for scheduling, we develop a novel multi-stage robust
approach with corrective action to ensure robust feasibility of the worst case solution
while reducing the conservatism arising from traditional robust optimization approaches.
We quantify the probability of constraint satisfaction by using a priori and a posteriori
probabilistic bounds for known and unknown uncertainty distributions, consequently, improving
the objective value for a given risk scenario. Computational experiments on several
examples were carried out to measure the effectiveness of the proposed method. For
a given constraint satisfaction probability, the proposed method improves the objective
value compared to the traditional robust optimization approaches
An Improved Robust Optimization Approach for Scheduling Under Uncertainty
In practice, the uncertainty in processing time data frequently affects the feasibility of
optimal solution of the nominal production scheduling problem. Using the unit-specific
event-based continuous time model for scheduling, we develop a novel multi-stage robust
approach with corrective action to ensure robust feasibility of the worst case solution
while reducing the conservatism arising from traditional robust optimization approaches.
We quantify the probability of constraint satisfaction by using a priori and a posteriori
probabilistic bounds for known and unknown uncertainty distributions, consequently, improving
the objective value for a given risk scenario. Computational experiments on several
examples were carried out to measure the effectiveness of the proposed method. For
a given constraint satisfaction probability, the proposed method improves the objective
value compared to the traditional robust optimization approaches
Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India
Abstract
Background
Verbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment.
Methods
We randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naïve Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one (4651) deaths were allocated to physician (standard), and 4723 to automated arms.
Results
The two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79–45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm.
Conclusions
While desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths.
Trial registration
ClinicalTrials.gov
, NCT02810366. Submitted on 11 April 2016