Metamodel variability analysis combining bootstrapping and validation techniques

Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of the EOQ model show encouraging results

Dynamic Objectives Aggregation in Multi-objective Evolutionary Optimization

Several approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This paper proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum aggregations and curvature variations. A comparison analysis is presented on the basis of a campaign of computational experiments on a set of benchmark problems from the literature.Multi-objective optimization, Evolutionary algorithms, Aggregate objective functions

DOAM for Evolutionary Portfolio Optimization: a computational study.

In this work, the ability of the Dynamic Objectives Aggregation Methods to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the simultaneously optimization of the risk on portfolio, the expected return and the transaction cost.

Robust Optimization in Simulation: Taguchi and Response Surface Methodology

Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a 'robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by Response Surface Methodology (RSM). George Box originated RSM, and Douglas Montgomery recently extended RSM to robust optimization of real (non-simulated) systems. We combine Taguchi's view with RSM for simulated systems, and apply the resulting methodology to classic Economic Order Quantity (EOQ) inventory models. Our results demonstrate that in general robust optimization requires order quantities that differ from the classic EOQ.Pareto frontier;bootstrap;Latin hypercube sampling

An efficient decomposition approach for surgical planning

This talk presents an efficient decomposition approach to surgical planning. Given a set of surgical waiting lists (one for each discipline) and an operating theater, the problem is to decide the room-to-discipline assignment for the next planning period (Master Surgical Schedule), and the surgical cases to be performed (Surgical Case Assignment), with the objective of optimizing a score related to priority and current waiting time of the cases. While in general MSS and SCA may be concurrently found by solving a complex integer programming problem, we propose an effective decomposition algorithm which does not require expensive or sophisticated computational resources, and is therefore suitable for implementation in any real-life setting. Our decomposition approach consists in first producing a number of subsets of surgical cases for each discipline (potential OR sessions), and select a subset of them. The surgical cases in the selected potential sessions are then discarded, and only the structure of the MSS is retained. A detailed surgical case assignment is then devised filling the MSS obtained with cases from the waiting lists, via an exact optimization model. The quality of the plan obtained is assessed by comparing it with the plan obtained by solving the exact integrated formulation for MSS and SCA. Nine different scenarios are considered, for various operating theater sizes and management policies. The results on instances concerning a medium-size hospital show that the decomposition method produces comparable solutions with the exact method in much smaller computation time

COVID-19 vaccine: factual reporting, dynamic preferences, and gender hesitancy

At different rates in different countries, one can observe the phenomenon of COVID-19 vaccine hesitancy. In June 2021, we surveyed 1,068 people in France and Italy to inquire about individual potential acceptance, focusing on time preferences, in a risk-return framework: getting the jab today, in a month, and in 3 months; perceived risks of vaccination and COVID-19; and expected benefit of the vaccine. We conducted a randomized controlled trial to understand the impact of daily stimuli, such as factual news about vaccines, on audience acceptance of vaccination. In the main experiment, participants were asked to read two different articles extracted from two Italian newspapers about vaccine-related thrombosis, one using a more abstract description and language and the other using a more anecdotical description and concrete language. We find that individual preferences for vaccination are variable and unstable over time, and individual choices of accepting, refusing, or delaying may be affected by the way news is written. To understand these dynamic preferences, we propose a new model based on seven categories of human behaviours that was validated by a neural network. We observe a treatment effect: participants who red the articles significantly shifted to vaccine hesitancy categories. Furthermore, we detect a peculiar gender effect, showing that the type of language that results in a higher vaccination rate for men is correlated with women’s lower vaccination rate and vice versa. This outcome should be taken into consideration for an appropriate gender-based communication campaign to achieve herd immunity

Release of paused RNA polymerase II at specific loci favors DNA double-strand-break formation and promotes cancer translocations

It is not clear how spontaneous DNA double-strand breaks (DSBs) form and are processed in normal cells, and whether they predispose to cancer-associated translocations. We show that DSBs in normal mammary cells form upon release of paused RNA polymerase II (Pol II) at promoters, 5′ splice sites and active enhancers, and are processed by end-joining in the absence of a canonical DNA-damage response. Logistic and causal-association models showed that Pol II pausing at long genes is the main predictor and determinant of DSBs. Damaged introns with paused Pol II-pS5, TOP2B and XRCC4 are enriched in translocation breakpoints, and map at topologically associating domain boundary-flanking regions showing high interaction frequencies with distal loci. Thus, in unperturbed growth conditions, release of paused Pol II at specific loci and chromatin territories favors DSB formation, leading to chromosomal translocations

Reconstruction of the geometry of volcanic vents by trajectory tracking of fast ejecta - the case of the Eyjafjallajökull 2010 eruption (Iceland)

Two methods are introduced to estimate the depth of origin of ejecta trajectories (depth to magma level in conduit) and the diameter of a conduit in an erupting crater, using analysis of videos from the Eyjafjallajökull 2010 eruption to evaluate their applicability. Both methods rely on the identification of straight, initial trajectories of fast ejecta, observed near the crater rims before they are appreciably bent by air drag and gravity. In the first method, through tracking these straight trajectories and identifying a cut-off angle, the inner diameter and the depth level of the vent can be constrained. In the second method, the intersection point of straight trajectories from individual pulses is used to determine the maximum possible depth from which the tracked ejecta originated and the width of the region from which the pulses emanated. The two methods give nearly identical results on the depth to magma level in the crater of Eyjafjallajökull on 8 to 10 May of 51 ± 7 m. The inner vent diameter, at the level of origin of the pulses and ejecta, is found to have been 8 to 15 m. These methods open up the possibility to feed (near) real-time monitoring systems with otherwise inaccessible information about vent geometry during an ongoing eruption and help defining important eruption source parameters