A soft robust model for optimization under ambiguity

In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.

Environmental and genetic determinants of colony morphology in yeast.

Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs.

Optimization of treatment strategy used during shockwave lithotripsy to maximize stone fragmentation efficiency.

BACKGROUND AND PURPOSE: Previous studies have demonstrated that treatment strategy plays a critical role in ensuring maximum stone fragmentation during shockwave lithotripsy (SWL). We aimed to develop an optimal treatment strategy in SWL to produce maximum stone fragmentation. MATERIALS AND METHODS: Four treatment strategies were evaluated using an in-vitro experimental setup that mimics stone fragmentation in the renal pelvis. Spherical stone phantoms were exposed to 2100 shocks using the Siemens Modularis (electromagnetic) lithotripter. The treatment strategies included increasing output voltage with 100 shocks at 12.3 kV, 400 shocks at 14.8 kV, and 1600 shocks at 15.8 kV, and decreasing output voltage with 1600 shocks at 15.8 kV, 400 shocks at 14.8 kV, and 100 shocks at 12.3 kV. Both increasing and decreasing voltages models were run at a pulse repetition frequency (PRF) of 1 and 2 Hz. Fragmentation efficiency was determined using a sequential sieving method to isolate fragments less than 2 mm. A fiberoptic probe hydrophone was used to characterize the pressure waveforms at different output voltage and frequency settings. In addition, a high-speed camera was used to assess cavitation activity in the lithotripter field that was produced by different treatment strategies. RESULTS: The increasing output voltage strategy at 1 Hz PRF produced the best stone fragmentation efficiency. This result was significantly better than the decreasing voltage strategy at 1 Hz PFR (85.8% vs 80.8%, P=0.017) and over the same strategy at 2 Hz PRF (85.8% vs 79.59%, P=0.0078). CONCLUSIONS: A pretreatment dose of 100 low-voltage output shockwaves (SWs) at 60 SWs/min before increasing to a higher voltage output produces the best overall stone fragmentation in vitro. These findings could lead to increased fragmentation efficiency in vivo and higher success rates clinically.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Observations of spatial flow patterns at the coral colony scale on a shallow reef flat

Although small-scale spatial flow variability can affect both larger-scale circulation patterns and biological processes on coral reefs, there are few direct measurements of spatial flow patterns across horizontal scales <100 m. Here flow patterns on a shallow reef flat were measured at scales from a single colony to several adjacent colonies using an array of acoustic Doppler velocimeters on a diver-operated traverse. We observed recirculation zones immediately behind colonies, reduced currents and elevated dissipation rates in turbulent wakes up to 2 colony diameters downstream and enhanced Reynolds stresses in shear layers around wake peripheries. Flow acceleration zones were observed above and between colonies. Coherent flow structures varied with incident flow speeds; recirculation zones were stronger and wakes were more turbulent in faster flows. Low-frequency (<0.03 Hz) flow variations, for which water excursions were large compared with the colony diameters (Keulegan-Carpenter number, KC >1), had similarspatial patterns to wakes, while higher-frequency variations (0.05-0.1 Hz, KC<1) had no observable spatial structure. On the reef flat, both drag and inertial forces exerted by coral colonies could have significant effects on flow, but within different frequency ranges; drag dominates for low-frequency flow variations and inertial forces dominate for higher frequency variations, including the wave band. Our scaling analyses suggest that spatial flow patterns at colony and patch scales could have important implications or both physical and biological processes at larger reef scales through their effects on forces exerted on the flow, turbulent mixing, and dispersion. © 2013. American Geophysical Union. All Rights Reserved.

CT Scan Dosimetric Parameters Routine Monitoring: First Results of Radiation Dose Optimization Strategies Promptly Provided by a Multidisciplinary Team

CONCLUSION Radiation dose reduction, while saving image quality could be easily implemented with this approach. Furthermore, the availability of a dosimetric data archive provides immediate feedbacks, related to the implemented optimization strategies. Background JCI Standards and European Legislation (EURATOM 59/2013) require the implementation of patient radiation protection programs in diagnostic radiology. Aim of this study is to demonstrate the possibility to reduce patients radiation exposure without decreasing image quality, through a multidisciplinary team (MT), which analyzes dosimetric data of diagnostic examinations. Evaluation Data from CT examinations performed with two different scanners (Siemens DefinitionTM and GE LightSpeed UltraTM) between November and December 2013 are considered. CT scanners are configured to automatically send images to DoseWatch© software, which is able to store output parameters (e.g. kVp, mAs, pitch ) and exposure data (e.g. CTDIvol, DLP, SSDE). Data are analyzed and discussed by a MT composed by Medical Physicists and Radiologists, to identify protocols which show critical dosimetric values, then suggest possible improvement actions to be implemented. Furthermore, the large amount of data available allows to monitor diagnostic protocols currently in use and to identify different statistic populations for each of them. Discussion We identified critical values of average CTDIvol for head and facial bones examinations (respectively 61.8 mGy, 151 scans; 61.6 mGy, 72 scans), performed with the GE LightSpeed CTTM. Statistic analysis allowed us to identify the presence of two different populations for head scan, one of which was only 10% of the total number of scans and corresponded to lower exposure values. The MT adopted this protocol as standard. Moreover, the constant output parameters monitoring allowed us to identify unusual values in facial bones exams, due to changes during maintenance service, which the team promptly suggested to correct. This resulted in a substantial dose saving in CTDIvol average values of approximately 15% and 50% for head and facial bones exams, respectively. Diagnostic image quality was deemed suitable for clinical use by radiologists.

Incidence of febrile neutropenia and neutropenic infections in elderly patients receiving anthracycline-based chemotherapy for breast cancer without primary prophylaxis with colony-stimulating factors

There is concern about the potential increase of hematological toxicity in elderly patients treated with chemotherapy. Recently, primary prophylaxis with colony-stimulating factors (CSFs) was proposed for elderly patients receiving moderately toxic chemotherapy. However, evidence for the benefits of this primary prophylaxis for elderly breast cancer patients is currently lacking. We retrospectively analyzed the incidence of febrile neutropenia (FN) and neutropenic infections in elderly breast cancer patients receiving anthracycline-based chemotherapy without primary prophylaxis with colony-stimulating factors. In addition, we assessed the direct costs of hospitalization for these complications. Febrile neutropenia or neutropenic infection occurred in 13% of the 46 patients. Further studies are needed to adequately evaluate the risk of neutropenic complications (NC) in elderly patients receiving standard-dose chemotherapy for breast cancer and the potential benefits of primary prophylaxis with colony-stimulating factors. © 2004 Elsevier Ireland Ltd. All rights reserved.

Optimization and finite element analysis for reliable electronic packaging

This paper demonstrates a modeling and design approach that couples computational mechanics techniques with numerical optimisation and statistical models for virtual prototyping and testing in different application areas concerning reliability of eletronic packages. The integrated software modules provide a design engineer in the electronic manufacturing sector with fast design and process solutions by optimizing key parameters and taking into account complexity of certain operational conditions. The integrated modeling framework is obtained by coupling the multi-phsyics finite element framework - PHYSICA - with the numerical optimisation tool - VisualDOC into a fully automated design tool for solutions of electronic packaging problems. Response Surface Modeling Methodolgy and Design of Experiments statistical tools plus numerical optimisaiton techniques are demonstrated as a part of the modeling framework. Two different problems are discussed and solved using the integrated numerical FEM-Optimisation tool. First, an example of thermal management of an electronic package on a board is illustrated. Location of the device is optimized to ensure reduced junction temperature and stress in the die subject to certain cooling air profile and other heat dissipating active components. In the second example thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and subsequently used to optimise the life-time of solder interconnects under thermal cycling.

Fast divide-and-conquer algorithms for preemptive scheduling problems with controllable processing times - a polymatroid optimization approach

We consider a variety of preemptive scheduling problems with controllable processing times on a single machine and on identical/uniform parallel machines, where the objective is to minimize the total compression cost. In this paper, we propose fast divide-and-conquer algorithms for these scheduling problems. Our approach is based on the observation that each scheduling problem we discuss can be formulated as a polymatroid optimization problem. We develop a novel divide-and-conquer technique for the polymatroid optimization problem and then apply it to each scheduling problem. We show that each scheduling problem can be solved in $ \O({\rm T}_{\rm feas}(n) \times\log n)$ time by using our divide-and-conquer technique, where n is the number of jobs and Tfeas(n) denotes the time complexity of the corresponding feasible scheduling problem with n jobs. This approach yields faster algorithms for most of the scheduling problems discussed in this paper.

Optimization of an open-ended microwave oven for microelectronics packaging

A physically open, but electrically shielded, microwave open oven can be produced by virtue of the evanescent fields in a waveguide below cutoff. The below cutoff heating chamber is fed by a transverse magnetic resonance established in a dielectric-filled section of the waveguide exploiting continuity of normal electric flux. In order to optimize the fields and the performance of the oven, a thin layer of a dielectric material with higher permittivity is inserted at the interface. Analysis and synthesis of an optimized open oven predicts field enhancement in the heating chamber up to 9.4 dB. Results from experimental testing on two fabricated prototypes are in agreement with the simulated predictions, and demonstrate an up to tenfold improvement in the heating performance. The open-ended oven allows for simultaneous precision alignment, testing, and efficient curing of microelectronic devices, significantly increasing productivity gains.

Modelling and optimization of a pneumatic microfeeder system

This paper presents modelling and design optimization of a microfeeder which, as part of a microassembly system, is used for contactless object delivery. The microfeeder consists of an array of microactuators which are controlled by electrostatic actuation and used for maneuvering outcoming air jet for object hovering and delibery. The airflow behaviour in the microactuator is analysed by means of fluid mechanics and Computational Fluid Dynamics (CFD) simulation from three aspects, theoretical analysis, initial design assessment, and design modifications. The focus is put on the basic types of the microfeeder structure and the effects of structural details to the systematic performance. The structural pattern of the microactuator for forming airflow nozzle is identified and two design plans are proposed as basic structure patterns of pneumatic microactuators. The optimized design numerically shows the ability of delivering objects. This paper analyses the flow distribution pattern in microactuators and points out a way for effective design of pneumatic microfeeder systems. The optimization strategy provided by the present paper has close relevance to the design and manufacture of pneumatic microfeeder systems.