Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Agreed upon procedures report on the City of Springville, Iowa for the period July 1, 2007 through December 31, 2007

Agreed upon procedures report on the City of Springville, Iowa for the period July 1, 2007 through December 31, 2007

Rational reasoning or adaptive behavior? Evidence from two-person beauty contest games

Many experiments have shown that human subjects do not necessarily behave in line with game theoretic assumptions and solution concepts. The reasons for this non-conformity are multiple. In this paper we study the argument whether a deviation from game theory is because subjects are rational, but doubt that others are rational as well, compared to the argument that subjects, in general, are boundedly rational themselves. To distinguish these two hypotheses, we study behavior in repeated 2-person and many-person Beauty-Contest-Games which are strategically different from one another. We analyze four different treatments and observe that convergence toward equilibrium is driven by learning through the information about the other player s choice and adaptation rather than self-initiated rational reasoning.

Agreed upon procedures for the City of Garber for the year ended June 30, 2007

Agreed upon procedures for the City of Garber for the year ended June 30, 2007

Agreed upon procedures report on the City of Batavia, Iowa for the period July 1, 2005 through June 30, 2006

Agreed upon procedures report on the City of Batavia, Iowa for the period July 1, 2005 through June 30, 2006

Agreed upon procedures report on the City of Danbury, Iowa for the period July 1, 2006 through February 29, 2008

Agreed upon procedures report on the City of Danbury, Iowa for the period July 1, 2006 through February 29, 2008

Adaptive model selection using empirical complexities

Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

Agreed upon procedures report on the City of Clutier, Iowa for the period July 1, 2006 through March 31, 2007

Agreed upon procedures report on the City of Clutier, Iowa for the period July 1, 2006 through March 31, 2007

Building adaptive capacity and resilience to climate change in the water sector in Cape Verde

Purpose of the evaluation This is a scheduled standard mid-term evaluation (MTR) of a UNDP implemented GEF LDCF co-financed project. It is conducted by a team of an international and a national independent evaluator. The objective of the MTR, as set out in the Terms of Reference (TORs; Annex 1), is to provide an independent analysis of the progress of the project so far. The MTR aims to:  identify potential project design problems,  assess progress towards the achievement of the project objective and outcomes,  identify and document lessons learned (including lessons that might improve design and implementation of other projects, including UNDP-GEF supported projects), and  make recommendations regarding specific actions that should be taken to improve the project. The MTR is intended to assess signs of project success or failure and identify the necessary changes to be made. The project commenced its implementation in the first half of 2010 with the recruitment of project staff. According to the updated project plan, it is due to close in July 201410 with operations scaling down in December 2013 due to funding limits. Because of a slow implementation start, the mid-term evaluation was delayed to July 201311 The intended target audience of the evaluation are:  The project team and decision makers in the INGRH  The GEF and UNFCCC Operational Focal Points  The project partners and beneficiaries  UNDP in Cape Verde as well as the regional and headquarter (HQ) office levels  The GEF Secretariat.

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2008

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2008

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2007

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2007

ESCMID* guideline for the diagnosis and management of Candida diseases 2012: diagnostic procedures.

As the mortality associated with invasive Candida infections remains high, it is important to make optimal use of available diagnostic tools to initiate antifungal therapy as early as possible and to select the most appropriate antifungal drug. A panel of experts of the European Fungal Infection Study Group (EFISG) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) undertook a data review and compiled guidelines for the clinical utility and accuracy of different diagnostic tests and procedures for detection of Candida infections. Recommendations about the microbiological investigation and detection of candidaemia, invasive candidiasis, chronic disseminated candidiasis, and oropharyngeal, oesophageal, and vaginal candidiasis were included. In addition, remarks about antifungal susceptibility testing and therapeutic drug monitoring were made.

Stable sunspot equilibria in a cash-in-advance economy

We analyze a monetary model with flexible labor supply, cash-inadvance constraints and seigniorage-financed government deficits. If the intertemporal elasticity of substitution of labor is greater than one, there are two steady states, one determinate and the other indeterminate. If the elasticity is less than one, there is a unique steady state, which can be indeterminate. Only in the latter case do there exist sunspot equilibria that are stable under adaptive learning. A sufficient reduction in government purchases can in many cases eliminate the sunspot equilibria while raising consumption/labor taxes even enough to balance the budget may fail to achieve determinacy.

Agreed upon procedures report on the City of Ralston, Iowa for the period July 1, 2007 through August 31, 2008

Agreed upon procedures report on the City of Ralston, Iowa for the period July 1, 2007 through August 31, 2008

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.