It is shown how the phase-damping master equation, either in Markovian and non-Markovian regimes, can be obtained as an averaged random unitary evolution. This, apart from offering a common mathematical set-up for bot...
详细信息
It is shown how the phase-damping master equation, either in Markovian and non-Markovian regimes, can be obtained as an averaged random unitary evolution. This, apart from offering a common mathematical set-up for both regimes, enables us to solve this equation in a straightforward manner just by solving the Schrödinger equation and taking the stochastic expectation value of its solutions after an adequate modification. Using the linear entropy as a figure of merit (basically the loss of quantum coherence) four distinct kinds of environment are suggested.
In this paper, constrained stochastic optimization problems are considered for the case where the constraint functions are convex (but the criterion function can be non-convex) and where the criterion and constraint f...
详细信息
In this paper, constrained stochastic optimization problems are considered for the case where the constraint functions are convex (but the criterion function can be non-convex) and where the criterion and constraint functions are available only through their noisy observations. A general algorithm of the two time-scale stochastic approximation type is proposed for these problems. The proposed algorithm is applied to Markov decision problems with average cost, average constraints and parameterized stationary policy. The asymptotic behavior of the proposed algorithm is analyzed for the case where the algorithm step-sizes are constant and the noise in the observations of the criterion and constraint functions depends on the algorithm iterates.
Portfolio and risk management problems of power utilities may be modeled by multistage stochastic programs. These models use a set of scenarios and corresponding probabilities to model the multivariate random data pro...
详细信息
We analyze a network of dynamic agents where the topology of the network specifies the information flow between the agents. We present an analysis method for such a system for both consensus and formation stabilizatio...
详细信息
We analyze a network of dynamic agents where the topology of the network specifies the information flow between the agents. We present an analysis method for such a system for both consensus and formation stabilization problems. To consider the general features introduced by the information flow topology, we consider the case of agent dynamics being a single integrator. Then we show that the method of analysis can be extended to more general cases of complicated agent dynamics, non-ideal links for information flow, etc. We also consider the case when the topology of the network is changing over time. The focus of the paper is on obtaining conditions for the stability of the formation that can be checked in a decentralized way.
Mathematical models for the electricity portfolio management of a utility that owns a hydro-thermal generation system and trades on the power market often lead to complex stochastic optimization problems. We present a...
详细信息
Demand for supplies, such as ammunition, during a military operation is a scenario-dependent random variable that may be subject to high variance. The challenge is to design an efficient military logistics supply chai...
详细信息
Demand for supplies, such as ammunition, during a military operation is a scenario-dependent random variable that may be subject to high variance. The challenge is to design an efficient military logistics supply chain that satisfies uncertain, non-stationary demands, while taking into account the volatility and singularity of military operations. This research focuses on the development of a modeling framework that determines the optimal deployment of transportation assets and supplies at the operational level, with possible interdiction by enemy forces. We term this model, Optimal Military Logistics Supply Chain (OPTiMiLSC). This is a two-level, multiple time period scenario-based stochastic model. OPTiMiLSC uses a combination of optimization, scenario-based simulation and statistical analysis. We use a "scenario tree" method to generate the demand scenarios. The results show a positive correlation between the number of demand scenarios and the probability that a random demand scenario is satisfied. We compare OPTiMiLSC with two deterministic optimization approaches. The first approach is where demands are fixed at the 90 th percentile, which tends to over-supply when compared to OPTiMiLSC. The mean value approach, on the other hand, tends to under-supply. OPTiMiLSC enables military planners to establish a robust logistic plan that responds more adequately to an intra-theater operation.
作者：
Inuiguchi, MRamík, JUniv Ostrava
Inst Res & Appl Fuzzy Modeling Ostrava 70103 Czech Republic Osaka Univ
Grad Sch Engn Dept Elect & Informat Sci Suita Osaka 5650871 Japan
In this paper, we review some fuzzy linear programming methods and techniques from a practical point of view. In the first part, the general history and the approach of fuzzy mathematical programming are introduced. U...
详细信息
In this paper, we review some fuzzy linear programming methods and techniques from a practical point of view. In the first part, the general history and the approach of fuzzy mathematical programming are introduced. Using a numerical example, some models of fuzzy linear programming are described. In the second part of the paper, fuzzy mathematical programming approaches are compared to stochastic programming ones. The advantages and disadvantages of fuzzy mathematical programming approaches are exemplified in the setting of an optimal portfolio selection problem. Finally, some newly developed ideas and techniques in fuzzy mathematical programming are briefly reviewed. (C) 2000 Elsevier Science B.V. All rights reserved.
This paper considers a procedure of two-stage stochastic programming in which the performance function to be optimized is replaced by its empirical mean. This procedure converts a stochastic optimization problem into ...
详细信息
This paper considers a procedure of two-stage stochastic programming in which the performance function to be optimized is replaced by its empirical mean. This procedure converts a stochastic optimization problem into a deterministic one for which many methods are available. Another strength of the method is that there is essentially no requirement on the distribution of the random variables involved. Exponential convergence for the probability of deviation of the empirical optimum from the true optimum is established using large deviation techniques. Explicit bounds on the convergence rates are obtained for the case of quadratic performance functions. Finally, numerical results are presented for the famous news vendor problem, which lends experimental evidence supporting exponential convergence.
A brief overview is given of a new decision support system for solving deterministic resource decision problems. It is based on a synthesis of techniques of dynamic programming and linear programming - hence the acron...
详细信息
A brief overview is given of a new decision support system for solving deterministic resource decision problems. It is based on a synthesis of techniques of dynamic programming and linear programming - hence the acronym DLP. The main purpose of the article is to develop an extension that incorporates uncertainty of information in production and objective coefficients. The resulting model/algorithm - a new method for chance-constrained stochastic linear programming - unites techniques of stochastic dynamic programming with techniques of linear programming, and it can be implemented by building very directly on the DLP decision support system. A further extension is introduced more briefly. Its combination of chance constraints and recourse (simple or complete) constitutes a fundamental new approach to stochastic programming, one that is likely to be appropriate for many multiperiod, resource-planning problems under uncertainty. The discussion is illustrated throughout using rangeland resource decision problems, A self-contained appendix provides a supplementary illustration for a highway pavement maintenance and rehabilitation problem.
In several real-world applications, modelled by two-stage stochastic problems, first and second-stage decisions (or some of their components) represent identical variables of the problem that is modelled. In these cas...
详细信息
In several real-world applications, modelled by two-stage stochastic problems, first and second-stage decisions (or some of their components) represent identical variables of the problem that is modelled. In these cases an appropriate solution of the problem might require that the second-stage decisions do not differ substantially from the corresponding first-stage ones. In this paper we propose a parametric approach to control the variability of the first and second-stage decisions and present a suitable solution framework. The advantage of the new approach is illustrated by considering two specific applications in electric power management and financial planning
暂无评论