While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a...
ming. The theory and methods of solving stochastic integer programming problems draw heavily fromthe theory of general integer programming. Their comprehensive presentation would entail discussion of many concepts and methods of this vast field, which would have little connection with the rest of the...
Modeling with Itô Stochastic Differential Equations is useful for researchers and graduate students. As a textbook for a graduate course, prerequisites include probability theory, differential equations, intermediate analysis, and some knowledge of scientific programming.Similar...
参考文献[2]将SO在SVRP中的应用分为Apriori paradigm和reoptimization。前者也被称为stochastic programming with recourse。Apriori将问题改变成两阶段问题: 其中Q ( x , ξ )代表x和ξ实现之后recourse的期望成本。在第一阶段,我们首先根据参数的期望值构造一个解。在第二阶段,如果随机变量的实现值使得该解违背了...
Models are quickly constructed using the modeling libraries, simulated with the appropriate model of computation and analyzed with the generated reports. To support accurate modeling, the Block Diagram Editor has error detection and reporting, syntax checkers, graphical debuggers, tracing and logging. ...
Mixed integer linear programmingStochastic diffusion search algorithmLeftoversMarble industryIn this study, one-dimensional marble plane cutting problem is studied based on the cutting equipment productivity and effective use of marble blocks. Different types of marble planes should be cut from multiple ...
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Stochastic programming in production planning: a case with none-simple recourse In modeling real world planning problems as optimization programs the assumption that all parameters are known with certainty is often more seriously viola... ROBERTJ.,PETERS,KLAAS,... - 《Statistica Neerlandica》 被引量...
There is also the broadest set of transit assignment methods including some innovative methods not found in other packages. These include a stochastic user equilibrium method that deals with multiple service alternatives, vehicle capacity, and optionally with dwell time and user’s value of time. In...
[92] explored existing optimization techniques for dealing with uncertainty, such as recourse-based stochastic programming, risk-averse stochastic programming, robust optimization, and fuzzy mathematical programming in terms of mathematical modeling and solution approaches. Refs. [93,94,95,96,97,98] ...