A new mixed-integer modeling approach for capacity-constrained continuous-time scheduling problems

Nowadays, scheduling and resource management are increasingly important issues for organizations. Indeed, they do not only constitute an underlying necessity to make things work properly within the companies, but are and will always be more critical means to reduce costs and get competitive advantage in the market. Different approaches have been typically employed for these problems during the years. Among the others, linear programming techniques represent a valid tool that, despite applicable only to instances of limited dimension, offers an extremely flexible modeling opportunity, able to produce either optimal or approximate solutions of certified quality. In this spirit, the definition of suitable indicator variables and the use of particular constraints are proposed in the present work, with the aim of providing a useful basis for different mathematical models, taking into account scarce resources and other potential limitations. More in detail, a very well-known problem from the literature, the Resource Constrained Project Scheduling Problem, is investigated, and a new mixed-integer linear formulation is introduced, which treats time as a continuous variable. The considered model presents several advantages from the computational point of view, that are deeply studied and compared with those of one of the best methods recently developed in the same field. Extensive experiments reveal the good performances achieved by the proposed formulation over all the KPIs included in the analysis, thus motivating further applications to derived problems, such as the workforce planning and scheduling framework presented at the end of this dissertation

A simheuristic algorithm for solving an integrated resource allocation and scheduling problem

Modern companies have to face challenging configuration issues in their manufacturing chains. One of these challenges is related to the integrated allocation and scheduling of resources such as machines, workers, energy, etc. These integrated optimization problems are difficult to solve, but they can be even more challenging when real-life uncertainty is considered. In this paper, we study an integrated allocation and scheduling optimization problem with stochastic processing times. A simheuristic algorithm is proposed in order to effectively solve this integrated and stochastic problem. Our approach relies on the hybridization of simulation with a metaheuristic to deal with the stochastic version of the allocation-scheduling problem. A series of numerical experiments contribute to illustrate the efficiency of our methodology as well as their potential applications in real-life enterprise settings

Prediction of early recurrent thromboembolic event and major bleeding in patients with acute stroke and atrial fibrillation by a risk stratification schema: the ALESSA score study

Background and Purposes—This study was designed to derive and validate a score to predict early ischemic events and major bleedings after an acute ischemic stroke in patients with atrial fibrillation. Methods—The derivation cohort consisted of 854 patients with acute ischemic stroke and atrial fibrillation included in prospective series between January 2012 and March 2014. Older age (hazard ratio 1.06 for each additional year; 95% confidence interval, 1.00–1.11) and severe atrial enlargement (hazard ratio, 2.05; 95% confidence interval, 1.08–2.87) were predictors for ischemic outcome events (stroke, transient ischemic attack, and systemic embolism) at 90 days from acute stroke. Small lesions (≤1.5 cm) were inversely correlated with both major bleeding (hazard ratio, 0.39; P=0.03) and ischemic outcome events (hazard ratio, 0.55; 95% confidence interval, 0.30–1.00). We assigned to age ≥80 years 2 points and between 70 and 79 years 1 point; ischemic index lesion >1.5 cm, 1 point; severe atrial enlargement, 1 point (ALESSA score). A logistic regression with the receiver-operating characteristic graph procedure (C statistic) showed an area under the curve of 0.697 (0.632–0.763; P=0.0001) for ischemic outcome events and 0.585 (0.493–0.678; P=0.10) for major bleedings. Results—The validation cohort consisted of 994 patients included in prospective series between April 2014 and June 2016. Logistic regression with the receiver-operating characteristic graph procedure showed an area under the curve of 0.646 (0.529–0.763; P=0.009) for ischemic outcome events and 0.407 (0.275–0.540; P=0.14) for hemorrhagic outcome events. Conclusions—In acute stroke patients with atrial fibrillation, high ALESSA scores were associated with a high risk of ischemic events but not of major bleedings

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Anticoagulation After Stroke in Patients With Atrial Fibrillation : To Bridge or Not With Low-Molecular-Weight Heparin?

Background and Purpose- Bridging therapy with low-molecular-weight heparin reportedly leads to a worse outcome for acute cardioembolic stroke patients because of a higher incidence of intracerebral bleeding. However, this practice is common in clinical settings. This observational study aimed to compare (1) the clinical profiles of patients receiving and not receiving bridging therapy, (2) overall group outcomes, and (3) outcomes according to the type of anticoagulant prescribed. Methods- We analyzed data of patients from the prospective RAF and RAF-NOACs studies. The primary outcome was defined as the composite of ischemic stroke, transient ischemic attack, systemic embolism, symptomatic cerebral bleeding, and major extracerebral bleeding observed at 90 days after the acute stroke. Results- Of 1810 patients who initiated oral anticoagulant therapy, 371 (20%) underwent bridging therapy with full-dose low-molecular-weight heparin. Older age and the presence of leukoaraiosis were inversely correlated with the use of bridging therapy. Forty-two bridged patients (11.3%) reached the combined outcome versus 72 (5.0%) of the nonbridged patients (P=0.0001). At multivariable analysis, bridging therapy was associated with the composite end point (odds ratio, 2.3; 95% CI, 1.4-3.7; P Conclusions- Our findings suggest that patients receiving low-molecular-weight heparin have a higher risk of early ischemic recurrence and hemorrhagic transformation compared with nonbridged patients.Peer reviewe