In this paper we consider the problem of computing decentralized control policies in a discrete stochastic decision problem. For the problem we consider, computation of optimal decentralized policies is NP-hard. We pr...
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ISBN:
(纸本)0780390989
In this paper we consider the problem of computing decentralized control policies in a discrete stochastic decision problem. For the problem we consider, computation of optimal decentralized policies is NP-hard. We present a relaxation method for this problem which computes suboptimal decentralized policies as well as bounds on the optimal achievable value. We then show that policies computed from this relaxation are guaranteed to be within a fixed bound of optimal. The relaxation is derived from an equivalent formulation of this decentralized decision problem as a polynomial optimization problem. The method is illustrated by an example of decentralized detection.
When evaluating the performance of a stochastic optimizer it is sometimes desirable to express peformance in terms of the quality attained in a certain fraction of sample runs. For example, the sample median quality i...
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ISBN:
(纸本)0769522866
When evaluating the performance of a stochastic optimizer it is sometimes desirable to express peformance in terms of the quality attained in a certain fraction of sample runs. For example, the sample median quality is the best estimator of what one would expect to achieve in 50% of runs, and similarly for other quantiles. In multiobjective optimization, the notion still applies but the outcome of a run is measured not as a scalar (i.e. the cost of the best solution), but as an attainment surface in k-dimensional space (where k is the number of objectives). In this paper we report an algorithm that can be conveniently used to plot summary attainment surfaces in any number of dimensions (though it is particularly suited for three). A summary attainment surface is defined as the union of all tightest goals that have been attained (independently) in precisely s of the runs of a sample of n runs, for any s epsilon 1..n, and for any k. We also discuss the computational complexity of the algorithm and give some examples of its use. C code for the algorithm is available from the author.
Uncertainty is one of the characteristics of product recovery networks. in particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present a st...
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Uncertainty is one of the characteristics of product recovery networks. in particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present a stochastic programming based approach by which a deterministic location model for product recovery network design may be extended to explicitly account for the uncertainties. Such a stochastic model seeks a solution which is appropriately balanced between some alternative scenarios identified by field experts. We apply the stochastic models to a representative real case study on recycling sand from demolition waste in The Netherlands. The interpretation of the results is meant to give more insight into decision-making under uncertainty for reverse logistics. (C) 2003 Elsevier B.V. All rights reserved.
Recent decades viewed increasing interests in the subject of decentralized decision-making. In this paper, three definitions of stochastic Nash equilibrium, which casts different decision criteria, are proposed for a ...
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ISBN:
(纸本)3540259120
Recent decades viewed increasing interests in the subject of decentralized decision-making. In this paper, three definitions of stochastic Nash equilibrium, which casts different decision criteria, are proposed for a stochastic decentralized decision system. Then the problem of how to find the stochastic Nash equilibrium is converted to an optimization problem. Lastly, a solution method combined with neural network and genetic algorithm is provided.
We propose an SOS transition rule format for the generative model of probabilistic processes. Transition rules are partitioned in several strata, giving rise to an ordering relation analogous to those introduced by Ul...
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ISBN:
(数字)9783540319825
ISBN:
(纸本)3540253882
We propose an SOS transition rule format for the generative model of probabilistic processes. Transition rules are partitioned in several strata, giving rise to an ordering relation analogous to those introduced by Ulidowski and Phillips for classic process algebras. Our rule format guarantees that probabilistic bisimulation is a congruence w.r.t. process algebra operations. Moreover, our rule format guarantees that process algebra operations preserve semistochasticity of processes, i.e. the property that the sum of the probability of the moves of any process is either 0 or 1. Finally, we show that most of operations of the probabilistic process algebras studied in the literature are captured by our format, which, therefore, has practical applications.
We study the interaction between non-deterministic and probabilistic behaviour in systems with continuous state spaces, arbitrary probability distributions and uncountable branching. Models of such systems have been p...
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ISBN:
(数字)9783540319825
ISBN:
(纸本)3540253882
We study the interaction between non-deterministic and probabilistic behaviour in systems with continuous state spaces, arbitrary probability distributions and uncountable branching. Models of such systems have been proposed previously. Here, we introduce a model that extends probabilistic automata to the continuous setting. We identify the class of schedulers that ensures measurability properties on executions, and show that such measurability properties are preserved by parallel composition. Finally, we demonstrate how these results allow us to define an alternative notion of weak bisimulation in our model.
We apply stochastic bounding methods with a partial order on the state space to the analysis of memory overflow in a router. Usually, stochastic bounds are associated to a total order implying useless constraints and ...
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ISBN:
(纸本)3540294147
We apply stochastic bounding methods with a partial order on the state space to the analysis of memory overflow in a router. Usually, stochastic bounds are associated to a total order implying useless constraints and decreasing the tightness of bounds. Here we present the basic methodology of sample path comparison with a partial order and some numerical results to show the accuracy of the results. We analyze the probability of a buffer overflow with two types of packets, a Pushout access mechanism and Markov modulated batch arrivals. This problem is strongly related to the memory rejection out a Fiber Delay Loop in an all optical router using deflection routing.
In the computation of aeroacoustic noise, both the Lighthill analogy and the linearized Euler approaches require the definition of source terms involving instantaneous flow fluctuations, which are generally obtained f...
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ISBN:
(纸本)0791841987
In the computation of aeroacoustic noise, both the Lighthill analogy and the linearized Euler approaches require the definition of source terms involving instantaneous flow fluctuations, which are generally obtained from either Direct Numerical Simulation (DNS) or Large Eddy Simulation (LES). However, these approaches are not economically viable in terms of computational resources, as they require very fine grids to deliver accurate results. Therefore, the stochastic Velocity Field generation model (SVFG) has has been applied in this paper. The SVFG model is based on the concept of the stochastic Noise Generation and Radiation (SNGR) without sound propagation and linearized equations. The SVFG model uses time-averaged quantities from the Reynolds Averaged Navier-Stokes equations (RANS) to generate a synthetic time dependent turbulent flow field. The turbulent fluctuations are modeled using a stochastic description of the three-dimensional turbulent motion with a discrete set of Fourier modes. This synthetic turbulent field represents many of the characteristics of real turbulence. Nevertheless, it still has some imperfections;although it exhibits the expected correlation length and the required ratio of length scales, it does not predict the convective properties of shear flow turbulence, as the approach generates homogenous and isotropic turbulence. These properties are shown in this paper with the test case of an axial-symmetrical subsonic jet. The SVFG model is used to generate the turbulent flow field, which then is used to compare with actual experiment measurement and other prediction methods. The results of the comparison show strengths and weaknesses of the model. Since the SVFG approach is relatively low cost when compared to both LES and DNS, it offers an attractive alternative to derive the turbulent flow field.
The main challenge of tracking articulated structures like hands is their many degrees of freedom (DOFs). A realistic 3-D model of the human hand has at least 26 DOFs. The arsenal of tracking approaches that can track...
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The main challenge of tracking articulated structures like hands is their many degrees of freedom (DOFs). A realistic 3-D model of the human hand has at least 26 DOFs. The arsenal of tracking approaches that can track such structures fast and reliably is still very small. This paper proposes a tracker based on stochastic meta-descent (SMD) for optimisations in such high-dimensional state spaces. This new algorithm is based on a gradient descent approach with adaptive and parameter-specific step sizes. The SMD tracker facilitates the integration of constraints, and combined with a stochastic sampling technique, can get out of spurious local minima. Furthermore, the integration of a deformable hand model based on linear blend skinning and anthropometrical measurements reinforces the robustness of the tracker. Experiments show the efficiency of the SMD algorithm in comparison with common optimisation methods.
It is widely accepted that medium-term generation planning can be advantageously modeled through market equilibrium representation. There exist several methods to define and solve this kind of equilibrium in a determi...
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ISBN:
(纸本)0976131919
It is widely accepted that medium-term generation planning can be advantageously modeled through market equilibrium representation. There exist several methods to define and solve this kind of equilibrium in a deterministic way. Medium-term planning is strongly affected by uncertainty in market and system conditions;thus, extensions of these models are commonly required. The main variables that should be considered as subject to uncertainty include hydro conditions, demand, generating units' failures, and fuel prices. This paper presents a model to represent a rnedium-term operation of the electrical market that introduces this uncertainty in the formulation in a natural and practical way. Utilities are explicitly considered to be maximizing their expected profits, and biddings are represented by means of a conjectural variation. Market equilibrium conditions are introduced by means of the optimality conditions of a problem, which has a structure that strongly resembles classical optimization of hydrothermal coordination. A tree-based representation tion to include stochastic variables and a model based on it are introduced. This approach to market representation provides three main advantages: Robust decisions are obtained;technical constraints are included in the problem in a natural way, additionally obtaining dual information;and large-size problerns representing real systems in detail can be addressed.
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