954 resultados para tabu search algorithm


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This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

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Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

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We propose a stylized model of a problem-solving organization whoseinternal communication structure is given by a fixed network. Problemsarrive randomly anywhere in this network and must find their way to theirrespective specialized solvers by relying on local information alone.The organization handles multiple problems simultaneously. For this reason,the process may be subject to congestion. We provide a characterization ofthe threshold of collapse of the network and of the stock of foatingproblems (or average delay) that prevails below that threshold. We buildupon this characterization to address a design problem: the determinationof what kind of network architecture optimizes performance for any givenproblem arrival rate. We conclude that, for low arrival rates, the optimalnetwork is very polarized (i.e. star-like or centralized ), whereas it islargely homogenous (or decentralized ) for high arrival rates. We also showthat, if an auxiliary assumption holds, the transition between these twoopposite structures is sharp and they are the only ones to ever qualify asoptimal.

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We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

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BACKGROUND: Internet is commonly used by the general population, notably for health information-seeking. There has been little research into its use by patients treated for a psychiatric disorder. AIM: To evaluate the use of internet by patients with psychiatric disorders in searching for general and medical information. METHODS: In 2007, 319 patients followed in a university hospital psychiatric out-patient clinic, completed a 28-items self-administered questionnaire. RESULTS: Two hundred patients surveyed were internet users. Most of them (68.5%) used internet in order to find health-related information. Only a small part of the patients knew and used criteria reflecting the quality of contents of the websites consulted. Knowledge of English and private Internet access were the factors significantly associated with the search of information on health on Internet. CONCLUSIONS: Internet is currently used by patients treated for psychiatric disorders, especially for medical seeking information.

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This paper advances a highly tractable model with search theoretic foundations for money and neoclassical growth. In the model, manufacturingand commerce are distinct and separate activities. In manufacturing,goods are efficiently produced combining capital and labor. In commerce,goods are exchanged in bilateral meetings. The model is applied to studythe effects of inßation on capital accumulation and welfare. With realisticparameters, inflation has large negative effects on welfare even though itraises capital and output. In contrast, with cash-in-advance, a deviceinformally motivated with bilateral trading, inflation depresses capitaland output and has a negligible effect on welfare.

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Our task in this paper is to analyze the organization of trading in the era of quantitativefinance. To do so, we conduct an ethnography of arbitrage, the trading strategy that bestexemplifies finance in the wake of the quantitative revolution. In contrast to value andmomentum investing, we argue, arbitrage involves an art of association - the constructionof equivalence (comparability) of properties across different assets. In place of essentialor relationa l characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else - associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

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This paper considers a job search model where the environment is notstationary along the unemployment spell and where jobs do not lastforever. Under this circumstance, reservation wages can be lower thanwithout separations, as in a stationary environment, but they can alsobe initially higher because of the non-stationarity of the model. Moreover,the time-dependence of reservation wages is stronger than with noseparations. The model is estimated structurally using Spanish data forthe period 1985-1996. The main finding is that, although the decrease inreservation wages is the main determinant of the change in the exit ratefrom unemployment for the first four months, later on the only effect comesfrom the job offer arrival rate, given that acceptance probabilities areroughly equal to one.

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A welfare analysis of unemployment insurance (UI) is performed in a generalequilibrium job search model. Finitely-lived, risk-averse workers smooth consumption over time by accumulating assets, choose search effort whenunemployed, and suffer disutility from work. Firms hire workers, purchasecapital, and pay taxes to finance worker benefits; their equity is the assetaccumulated by workers. A matching function relates unemployment, hiringexpenditure, and search effort to the formation of jobs. The model is calibrated to US data; the parameters relating job search effort to the probability of job finding are chosen to match microeconomic studies ofunemployment spells. Under logarithmic utility, numerical simulation shows rather small welfaregains from UI. Even without UI, workers smooth consumption effectivelythrough asset accumulation. Greater risk aversion leads to substantiallylarger welfare gains from UI; however, even in this case much of its welfareimpact is due not to consumption smoothing effects, but rather to decreased work disutility, or to a variety of externalities.

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In this paper I show how borrowing constraints and job search interact.I fit a dynamic model to data from the National Longitudinal Survey(1979-cohort) and show that borrowing constraints are significant. Agentswith more initial assets and more access to credit attain higher wagesfor several periods after high school graduation. The unemployed maintaintheir consumption by running down their assets, while the employed saveto buffer against future unemployment spells. I also show that, unlikein models with exogenous income streams, unemployment transfers, byallowing agents to attain higher wages do not 'crowd out' but increasesaving.

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This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

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Nominal Unification is an extension of first-order unification where terms can contain binders and unification is performed modulo α equivalence. Here we prove that the existence of nominal unifiers can be decided in quadratic time. First, we linearly-reduce nominal unification problems to a sequence of freshness and equalities between atoms, modulo a permutation, using ideas as Paterson and Wegman for first-order unification. Second, we prove that solvability of these reduced problems may be checked in quadràtic time. Finally, we point out how using ideas of Brown and Tarjan for unbalanced merging, we could solve these reduced problems more efficiently