125 resultados para Iterated


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This paper proposes a model of choice that does not assume completeness of the decision maker’s preferences. The model explains in a natural way, and within a unified framework of choice when preference-incomparable options are present, four behavioural phenomena: the attraction effect, choice deferral, the strengthening of the attraction effect when deferral is per-missible, and status quo bias. The key element in the proposed decision rule is that an individual chooses an alternative from a menu if it is worse than no other alternative in that menu and is also better than at least one. Utility-maximising behaviour is included as a special case when preferences are complete. The relevance of the partial dominance idea underlying the proposed choice procedure is illustrated with an intuitive generalisation of weakly dominated strategies and their iterated deletion in games with vector payoffs.

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We discuss necessary as well as sufficient conditions for the second iterated local multiplier algebra of a separable C*-algebra to agree with the first.

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This Health Strategy points to the need for promoting healthy ageing in conjunction with the then National Council for Elderly – a goal which was re-iterated in the 1995 Health Promotion Strategy, in which older people were identified as a priority  population group with particular health promotion needs  

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Many animals that live in groups maintain competitive relationships, yet avoid continual fighting, by forming dominance hierarchies. We compare predictions of stochastic, individual-based models with empirical experimental evidence using shore crabs to test competing hypotheses regarding hierarchy development. The models test (1) what information individuals use when deciding to fight or retreat, (2) how past experience affects current resource-holding potential, and (3) how individuals deal with changes to the social environment. First, we conclude that crabs assess only their own state and not their opponent's when deciding to fight or retreat. Second, willingness to enter, and performance in, aggressive contests are influenced by previous contest outcomes. Winning increases the likelihood of both fighting and winning future interactions, while losing has the opposite effect. Third, when groups with established dominance hierarchies dissolve and new groups form, individuals reassess their ranks, showing no memory of previous rank or group affiliation. With every change in group composition, individuals fight for their new ranks. This iterative process carries over as groups dissolve and form, which has important implications for the relationship between ability and hierarchy rank. We conclude that dominance hierarchies emerge through an interaction of individual and social factors, and discuss these findings in terms of an underlying mechanism. Overall, our results are consistent with crabs using a cumulative assessment strategy iterated across changes in group composition, in which aggression is constrained by an absolute threshold in energy spent and damage received while fighting.

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We present building blocks for algorithms for the efficient reduction of square factor, i.e. direct repetitions in strings. So the basic problem is this: given a string, compute all strings that can be obtained by reducing factors of the form zz to z. Two types of algorithms are treated: an offline algorithm is one that can compute a data structure on the given string in advance before the actual search for the square begins; in contrast, online algorithms receive all input only at the time when a request is made. For offline algorithms we treat the following problem: Let u and w be two strings such that w is obtained from u by reducing a square factor zz to only z. If we further are given the suffix table of u, how can we derive the suffix table for w without computing it from scratch? As the suffix table plays a key role in online algorithms for the detection of squares in a string, this derivation can make the iterated reduction of squares more efficient. On the other hand, we also show how a suffix array, used for the offline detection of squares, can be adapted to the new string resulting from the deletion of a square. Because the deletion is a very local change, this adaption is more eficient than the computation of the new suffix array from scratch.

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Much of the current research in portland cement concrete (PCC) pavements deals with the analysis of early pavement life failures and seeks to find ways to prevent those from reoccurring. The Long Term Pavement Performance (LTPP) portion of the Strategic Highway Research Program (SHRP) has identified some of the key factors in designing and building new PCC pavements. This statement will build on the Iowa Highway Research Board (IHRB) project TR-463, Field Performance Study of Past Iowa Pavement Research: A Look Back. In Iowa and across the nation, there are multiple pavements that were built more than 20 years ago that have been and are continuing to provide very good service to the public. They are found on both state and local routes and in both low and high traffic volume areas. There is a need to learn what went into those pavements, from the subgrade through the surface, that makes them perform so well. The purpose of this research project was to conduct a scoping study that could be used to evaluate the need for additional research to study the attributes of well-performing concrete pavements. The concept of zero-maintenance jointed plain concrete pavements” was iterated in this study for long-lasting, well-performing portland cement concrete pavement sections. The scope of the study was limited to a brief literature survey, pavement performance data collection from many counties, cities, and primary and interstate roads in Iowa, field visits to many selected pavement sites, and analysis of the collected data. No laboratory orfield testing was conducted for this phase of the project. A problem statement with a research plan was created that could be used to guide the second phase of the project.

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From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

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We extend Aumann's theorem [Aumann 1987], deriving correlated equilibria as a consequence of common priors and common knowledge of rationality, by explicitly allowing for non-rational behavior. Wereplace the assumption of common knowledge of rationality with a substantially weaker one, joint p-belief of rationality, where agents believe the other agents are rational with probability p or more. We show that behavior in this case constitutes a kind of correlated equilibrium satisfying certain p-belief constraints, and that it varies continuously in the parameters p and, for p sufficiently close to one,with high probability is supported on strategies that survive the iterated elimination of strictly dominated strategies. Finally, we extend the analysis to characterizing rational expectations of interimtypes, to games of incomplete information, as well as to the case of non-common priors.

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Two main approaches are commonly used to empirically evaluate linear factor pricingmodels: regression and SDF methods, with centred and uncentred versions of the latter.We show that unlike standard two-step or iterated GMM procedures, single-step estimatorssuch as continuously updated GMM yield numerically identical values for prices of risk,pricing errors, Jensen s alphas and overidentifying restrictions tests irrespective of the modelvalidity. Therefore, there is arguably a single approach regardless of the factors being tradedor not, or the use of excess or gross returns. We illustrate our results by revisiting Lustigand Verdelhan s (2007) empirical analysis of currency returns.

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In today s highly competitive and global marketplace the pressure onorganizations to find new ways to create and deliver value to customersgrows ever stronger. In the last two decades, logistics and supply chainhas moved to the center stage. There has been a growing recognition thatit is through an effective management of the logistics function and thesupply chain that the goal of cost reduction and service enhancement canbe achieved. The key to success in Supply Chain Management (SCM) requireheavy emphasis on integration of activities, cooperation, coordination andinformation sharing throughout the entire supply chain, from suppliers tocustomers. To be able to respond to the challenge of integration there isthe need of sophisticated decision support systems based on powerfulmathematical models and solution techniques, together with the advancesin information and communication technologies. The industry and the academiahave become increasingly interested in SCM to be able to respond to theproblems and issues posed by the changes in the logistics and supply chain.We present a brief discussion on the important issues in SCM. We then arguethat metaheuristics can play an important role in solving complex supplychain related problems derived by the importance of designing and managingthe entire supply chain as a single entity. We will focus specially on theIterated Local Search, Tabu Search and Scatter Search as the ones, but notlimited to, with great potential to be used on solving the SCM relatedproblems. We will present briefly some successful applications.

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The problems arising in the logistics of commercial distribution are complexand involve several players and decision levels. One important decision isrelated with the design of the routes to distribute the products, in anefficient and inexpensive way.This article explores three different distribution strategies: the firststrategy corresponds to the classical vehicle routing problem; the second isa master route strategy with daily adaptations and the third is a strategythat takes into account the cross-functional planning through amulti-objective model with two objectives. All strategies are analyzed ina multi-period scenario. A metaheuristic based on the Iteratetd Local Search,is used to solve the models related with each strategy. A computationalexperiment is performed to evaluate the three strategies with respect to thetwo objectives. The cross functional planning strategy leads to solutions thatput in practice the coordination between functional areas and better meetbusiness objectives.

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This paper is concerned with the realism of mechanisms that implementsocial choice functions in the traditional sense. Will agents actually playthe equilibrium assumed by the analysis? As an example, we study theconvergence and stability properties of Sj\"ostr\"om's (1994) mechanism, onthe assumption that boundedly rational players find their way to equilibriumusing monotonic learning dynamics and also with fictitious play. Thismechanism implements most social choice functions in economic environmentsusing as a solution concept the iterated elimination of weakly dominatedstrategies (only one round of deletion of weakly dominated strategies isneeded). There are, however, many sets of Nash equilibria whose payoffs maybe very different from those desired by the social choice function. Withmonotonic dynamics we show that many equilibria in all the sets ofequilibria we describe are the limit points of trajectories that havecompletely mixed initial conditions. The initial conditions that lead tothese equilibria need not be very close to the limiting point. Furthermore,even if the dynamics converge to the ``right'' set of equilibria, it stillcan converge to quite a poor outcome in welfare terms. With fictitious play,if the agents have completely mixed prior beliefs, beliefs and play convergeto the outcome the planner wants to implement.

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We perform an experiment on a pure coordination game with uncertaintyabout the payoffs. Our game is closely related to models that have beenused in many macroeconomic and financial applications to solve problemsof equilibrium indeterminacy. In our experiment each subject receives anoisy signal about the true payoffs. This game has a unique strategyprofile that survives the iterative deletion of strictly dominatedstrategies (thus a unique Nash equilibrium). The equilibrium outcomecoincides, on average, with the risk-dominant equilibrium outcome ofthe underlying coordination game. The behavior of the subjects convergesto the theoretical prediction after enough experience has been gained. The data (and the comments) suggest that subjects do not apply through"a priori" reasoning the iterated deletion of dominated strategies.Instead, they adapt to the responses of other players. Thus, the lengthof the learning phase clearly varies for the different signals. We alsotest behavior in a game without uncertainty as a benchmark case. The gamewith uncertainty is inspired by the "global" games of Carlsson and VanDamme (1993).

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The need for integration in the supply chain management leads us to considerthe coordination of two logistic planning functions: transportation andinventory. The coordination of these activities can be an extremely importantsource of competitive advantage in the supply chain management. The battle forcost reduction can pass through the equilibrium of transportation versusinventory managing costs. In this work, we study the specific case of aninventory-routing problem for a week planning period with different types ofdemand. A heuristic methodology, based on the Iterated Local Search, isproposed to solve the Multi-Period Inventory Routing Problem with stochasticand deterministic demand.

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In this paper we provide a full characterization of the pure-strategyNash Equilibria for the p-Beauty Contest Game when we restrict player schoices to integer numbers. Opposed to the case of real number choices,equilibrium uniqueness may be lost depending on the value of p and thenumber of players: in particular, as p approaches 1 any symmetric profileconstitutes a Nash Equilibrium. We also show that any experimental p-BeautyContest Game can be associated to a game with the integer restriction andthus multiplicity of equilibria becomes an issue. Finally, we show thatin these games the iterated deletion of weakly dominated strategies maynot lead to a single outcome while the iterated best-reply process alwaysdoes (though the outcome obtained depends on the initial conditions).