Online Makespan Minimization with Parallel Schedules

In online makespan minimization a sequence of jobs $\sigma = J_1,..., J_n$ has to be scheduled on $m$ identical parallel machines so as to minimize the maximum completion time of any job. We investigate the problem with an essentially new model of resource augmentation. Here, an online algorithm is allowed to build several schedules in parallel while processing $\sigma$. At the end of the scheduling process the best schedule is selected. This model can be viewed as providing an online algorithm with extra space, which is invested to maintain multiple solutions. The setting is of particular interest in parallel processing environments where each processor can maintain a single or a small set of solutions. We develop a (4/3+\eps)-competitive algorithm, for any 0<\eps\leq 1, that uses a number of 1/\eps^{O(\log (1/\eps))} schedules. We also give a (1+\eps)-competitive algorithm, for any 0<\eps\leq 1, that builds a polynomial number of (m/\eps)^{O(\log (1/\eps) / \eps)} schedules. This value depends on $m$ but is independent of the input $\sigma$. The performance guarantees are nearly best possible. We show that any algorithm that achieves a competitiveness smaller than 4/3 must construct $\Omega(m)$ schedules. Our algorithms make use of novel guessing schemes that (1) predict the optimum makespan of a job sequence $\sigma$ to within a factor of 1+\eps and (2) guess the job processing times and their frequencies in $\sigma$. In (2) we have to sparsify the universe of all guesses so as to reduce the number of schedules to a constant. The competitive ratios achieved using parallel schedules are considerably smaller than those in the standard problem without resource augmentation

Role of unenhanced breast MRI for detecting and differentiating breast lesions

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The Neuropsychological Profile of Attention Deficits of Patients with Obstructive Sleep Apnea: An Update on the Daytime Attentional Impairment

none7noAbstract: Introduction: Patients with obstructive sleep apnea (OSA) suffer from several neurocognitive disturbances. One of the neuropsychological processes most investigated in OSA patients is attention, but the results have been controversial. Here, we update the attention profile of OSA patients with the final aim to improve attention assessment, with a possible impact on clinical and medical-legal practices, in terms of which attention subdomains and parameters need consideration and which one is a high-risk OSA phenotype for attention dysfunctions. Method: For this purpose, we assessed 32 previously untreated OSA patients (26 men and 6 women) under 65 years of age (mean age 53.2 ± 7.3; mean education level 10.4 ± 3.4 years) suffering from moderate to severe sleep apnea and hypopnea (mean apnea-hypopnea index (AHI) 45.3 ± 22.9, range 16.1–69.6). A control group of 34 healthy participants matched with OSA patients for age, education level, and general cognitive functioning were also enrolled. The OSA patients and healthy participants were tested through an extensive computerized battery (Test of Attentional Performance, TAP) that evaluated intensive (i.e., alertness and vigilance) and selective (i.e., divided and selective) dimensions of attention and returned different outcome parameters (i.e., reaction time, stability of performance, and various types of errors). Data analysis: The data were analyzed by ANCOVA which compared the speed and accuracy performance of the OSA and control participants (cognitive reserve was treated as a covariate). The possible mechanisms underlying attention deficits in OSA patients were examined through correlation analysis among AHI, oxygenation parameters, sleepiness scores, and TAP outcomes and by comparing the following three phenotypes of patients: severe OSA and severe nocturnal desaturators (AHI++D+), severe OSA nondesaturators (AHI++D−), and moderate OSA nondesaturators (AHI+D−). Results: The results suggest that the OSA patients manifest deficits in both intensive and selective attention processes and that reaction time (RT) alone is ineffective for detecting and characterizing their problems, for which error analysis and stability of performance also have to be considered. Patients with severe OSA and severe hypoxemia underperformed on alertness and vigilance attention subtests. Conclusions: The data suggest the importance of evaluating attention deficits among OSA patients through several parameters (including performance instability). Moreover, the data suggest a multifaceted mechanism underlying attention dysfunction in OSA patients.openAngelelli P., Macchitella L., Toraldo D.M., Abbate E., Marinelli C.V., Ariglian M., De Benedetto M.Angelelli, P.; Macchitella, L.; Toraldo, D. M.; Abbate, E.; Marinelli, C. V.; Ariglian, M.; De Benedetto, M

Comparison of policies in dynamic routing problems

We consider a company that has to satisfy customers' pick-up requests arriving over time every day. The overall objective of the company is to serve as many requests as possible at a minimum operational cost. When organizing its business the company has to fix some features of the service that may affect both service quality and operational costs. Some of these features concern the time a request is taken into account to plan its service, the associated deadline and the way requests are managed when the system is overloaded. In this paper we analyse several policies that can be implemented by the management of a carrier company in a multi-period context. For example, a company might reject all the requests that cannot be feasibly scheduled or accept all the requests and rely on a backup service in order to serve requests that are difficult to handle. Another interesting issue considered in this paper is the impact of collaborative service where two or more carrier companies, with their own customers, decide to share customers in order to optimize the overall costs. We set up a general framework to allow comparison of alternative service policies. Extensive computational results evaluating the number of lost requests and the distance travelled provide interesting insights

Dynamic Collection Scheduling Using Remote Asset Monitoring: Case Study in the UK Charity Sector

Remote sensing technology is now coming onto the market in the waste collection sector. This technology allows waste and recycling receptacles to report their fill levels at regular intervals. This reporting enables collection schedules to be optimized dynamically to meet true servicing needs in a better way and so reduce transport costs and ensure that visits to clients are made in a timely fashion. This paper describes a real-life logistics problem faced by a leading UK charity that services its textile and book donation banks and its high street stores by using a common fleet of vehicles with various carrying capacities. Use of a common fleet gives rise to a vehicle routing problem in which visits to stores are on fixed days of the week with time window constraints and visits to banks (fitted with remote fill-monitoring technology) are made in a timely fashion so that the banks do not become full before collection. A tabu search algorithm was developed to provide vehicle routes for the next day of operation on the basis of the maximization of profit. A longer look-ahead period was not considered because donation rates to banks are highly variable. The algorithm included parameters that specified the minimum fill level (e.g., 50%) required to allow a visit to a bank and a penalty function used to encourage visits to banks that are becoming full. The results showed that the algorithm significantly reduced visits to banks and increased profit by up to 2.4%, with the best performance obtained when the donation rates were more variable

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices

Multifunctional proteins revealed by overlapping clustering in protein interaction network

Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters