Modeling with Stochastic Programming (Springer Series in Operations Research and Financial Engineering)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...
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...
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...
Title:Stochastic Modeling and Control Author(s)Ivan Ganchev Ivanov Publisher:InTech (November 28, 2012); eBook (Creative Commons Licensed) License(s):Attribution 3.0 Unported (CC BY 3.0) Hardcover:294 pages eBook:PDF files, and a zipped PDF, 5.47 MB ...
Fig. 1. A stochastic frontier model of production. To also allow for such cases, we model the performance of firms’ production by means of stochastic frontier production model as follows: (2)Qit=Qit∗exp−uit where uit ≥ 0 is assumed to be i.i.d., with a half-normal distribution...
This book provides an essential introduction to Stochastic Programming,especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters,representing a decision problem under uncertainty. Several models for this problem are presented,including the main...
Mathematical program with equilibrium constraints NLP: Nonlinear programming NPV: Net present value NSGA: Nondominated sorting genetic algorithm OPF: Optimal power flow PDF: Probability distribution function PPO: Proximal policy optimization PSO: Particle swarm optimization QPP: Quadratic programmin...
models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. ...
This distribution of articles reveals that the popular trends in DOM research focus primarily on mathematical programming models with stochastic features for the preparedness and response phases, with many of them having a simulation component as well. Meanwhile the probabilistic and statistical methods we...
The stochastic version of CCP (sCCP [2]) is obtained by adding a stochastic duration to the instructions interacting with the constraint store C, i.e. ask and tell. More pre- cisely, each instruction is associated with a continuous random variable T, representing the time needed to perform...