978 resultados para Mixed binary nonlinear programming
Resumo:
Working Paper no longer available. Please contact the author.
Resumo:
The effectiveness of decision rules depends on characteristics of bothrules and environments. A theoretical analysis of environments specifiesthe relative predictive accuracies of the lexicographic rule 'take-the-best'(TTB) and other simple strategies for binary choice. We identify threefactors: how the environment weights variables; characteristics of choicesets; and error. For cases involving from three to five binary cues, TTBis effective across many environments. However, hybrids of equal weights(EW) and TTB models are more effective as environments become morecompensatory. In the presence of error, TTB and similar models do not predictmuch better than a naïve model that exploits dominance. We emphasizepsychological implications and the need for more complete theories of theenvironment that include the role of error.
Resumo:
We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.
Resumo:
Several studies have reported high performance of simple decision heuristics multi-attribute decision making. In this paper, we focus on situations where attributes are binary and analyze the performance of Deterministic-Elimination-By-Aspects (DEBA) and similar decision heuristics. We consider non-increasing weights and two probabilistic models for the attribute values: one where attribute values are independent Bernoulli randomvariables; the other one where they are binary random variables with inter-attribute positive correlations. Using these models, we show that good performance of DEBA is explained by the presence of cumulative as opposed to simple dominance. We therefore introduce the concepts of cumulative dominance compliance and fully cumulative dominance compliance and show that DEBA satisfies those properties. We derive a lower bound with which cumulative dominance compliant heuristics will choose a best alternative and show that, even with many attributes, this is not small. We also derive an upper bound for the expected loss of fully cumulative compliance heuristics and show that this is moderateeven when the number of attributes is large. Both bounds are independent of the values ofthe weights.
Resumo:
Common household cleaning products can cause injury when mixed. Some combinations produce harmful fumes and other dangerous by-products.
Resumo:
In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models.
Resumo:
We develop a mathematical programming approach for the classicalPSPACE - hard restless bandit problem in stochastic optimization.We introduce a hierarchy of n (where n is the number of bandits)increasingly stronger linear programming relaxations, the lastof which is exact and corresponds to the (exponential size)formulation of the problem as a Markov decision chain, while theother relaxations provide bounds and are efficiently computed. Wealso propose a priority-index heuristic scheduling policy fromthe solution to the first-order relaxation, where the indices aredefined in terms of optimal dual variables. In this way wepropose a policy and a suboptimality guarantee. We report resultsof computational experiments that suggest that the proposedheuristic policy is nearly optimal. Moreover, the second-orderrelaxation is found to provide strong bounds on the optimalvalue.
Resumo:
This paper examines competition in the standard one-dimensional Downsian model of two-candidate elections, but where one candidate (A) enjoys an advantage over the other candidate (D). Voters' preferences are Euclidean, but any voter will vote for candidate A over candidate D unless D is closer to her ideal point by some fixed distance \delta. The location of the median voter's ideal point is uncertain, and its distribution is commonly known by both candidates. The candidates simultaneously choose locations to maximize the probability of victory. Pure strategy equilibria often fails to exist in this model, except under special conditions about \delta and the distribution of the median ideal point. We solve for the essentially unique symmetric mixed equilibrium, show that candidate A adopts more moderate policies than candidate D, and obtain some comparative statics results about the probability of victory and the expected distance between the two candidates' policies.
Infestation and natural parasitism of aphids in single and mixed pastures of black oats and ryegrass
Resumo:
Some species of aphids are major pests on cereal crops and grass pastures. Usually these pests are not adequately controlled in pasture lands that become sources of aphid infestations to cereal crops. The dynamics of aphids and the incidence of natural enemies are less known in pasture systems than in cereal fields. The objective of this work was to assess the aphid infestation and natural aphid parasitism in different pasture composition. Three hypotheses were tested: 1- the aphid species composition in pastures may vary according to the cereal species in the field; 2- the mixture of two plant species can modify the amount and diversity of aphids; 3- the plant species composition of pasture fields influences the parasitism of aphids. Empirical data were obtained from three Poaceae fields: black oats (Avena strigosa L.), ryegrass (Lolium multiflorum L.), and a mixed field of black oats and ryegrass. The most abundant aphid species was Rhopalosiphum padi followed by Sitobion avenae. Plant species composition increases the amount and the parasitism rates of aphids. The mixture of heavily infested black oats with a poorly infested ryegrass resulted in reduction of aphid infestation in comparison with heavily-infested single plant species field. This is possible because the conditions are favorable for the development of parasitoid populations. Aphidius colemani was the main parasitoid found in these areas.
Resumo:
Combined prolactin (PRL) and growth hormone (GH) secretion by a single pituitary tumor can occur in approximately 5% of cases. However, in all previously reported patients, combined secretion of both hormones was present at the time of diagnosis. Here we describe a patient initially diagnosed with a pure prolactin-secreting microadenoma, who experienced the progressive apparition of symptomatic autonomous GH secretion while on intermittent long term dopamine agonist therapy. She was operated on, and immunohistochemical analysis of tumor tissue confirmed the diagnosis of pituitary adenoma with uniform co-staining of all cells for both GH and PRL. This patient represents the first documented occurrence of asynchronous development of combined GH and PRL secretion in a pituitary adenoma. Although pathogenic mechanisms implicated remain largely speculative, it emphasizes the need for long term hormonal follow up of patients harboring prolactinomas.
Resumo:
When can a single variable be more accurate in binary choice than multiple sources of information? We derive analytically the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide analogous derivations for multiple regression (MR) and equal weighting (EW) and specify the conditions under which the models differ in expected predictive ability. Key factors include variability in cue validities, intercorrelation between predictors, and the ratio of predictors to observations in MR. Theory and simulations are used to illustrate the differential effects of these factors. Results directly address why and when one-reason decision making can be more effective than analyses that use more information. We thus provide analytical backing to intriguing empirical results that, to date, have lacked theoretical justification. There are predictable conditions for which one should expect less to be more.
Resumo:
Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.
Resumo:
In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.
Resumo:
[Traditions. Asie. Inde. Madhya Pradesh. Baghelkhand]
Resumo:
Malignant mixed Müllerian tumours (malignant mixed mesodermal tumours, MMMT) of the uterus are metaplastic carcinomas with a sarcomatous component and thus they are also called carcinosarcomas. It has now been accepted that the sarcomatous component is derived from epithelial elements that have undergone metaplasia. The process that produces this metaplasia is epithelial to mesenchymal transition (EMT), which has recently been described as a neoplasia-associated programme shared with embryonic development and enabling neoplastic cells to move and metastasise. The ubiquitin proteasome system (UPS) regulates the turnover and functions of hundreds of cellular proteins. It plays important roles in EMT by being involved in the regulation of several pathways participating in the execution of this metastasis-associated programme. In this review the specifi c role of UPS in EMT of MMMT is discussed and therapeutic opportunities from UPS manipulations are proposed.