Author: Diana Schadl Yakowitz
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Two-stage Stochastic Linear Programming: Stochastic Decomposition Approaches (PHD).
Author: Diana Schadl Yakowitz
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Stochastic Decomposition
Author: Julia L. Higle
Publisher: Springer Science & Business Media
ISBN: 1461541158
Category : Mathematics
Languages : en
Pages : 237
Book Description
Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved using LP software. However, there are many applications, such as the telecommunications planning problem discussed in this book, where a handful of seenarios do not capture variability well enough to provide a reasonable model of the actual decision-making problem. Problems of this type easily exceed the capabilities of LP software by several orders of magnitude. Their solution requires the use of algorithmic methods that exploit the structure of the SLP model in a manner that will accommodate large scale applications.
Publisher: Springer Science & Business Media
ISBN: 1461541158
Category : Mathematics
Languages : en
Pages : 237
Book Description
Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved using LP software. However, there are many applications, such as the telecommunications planning problem discussed in this book, where a handful of seenarios do not capture variability well enough to provide a reasonable model of the actual decision-making problem. Problems of this type easily exceed the capabilities of LP software by several orders of magnitude. Their solution requires the use of algorithmic methods that exploit the structure of the SLP model in a manner that will accommodate large scale applications.
Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming
Author: Christian Küchler
Publisher: Springer Science & Business Media
ISBN: 3834893994
Category : Mathematics
Languages : en
Pages : 178
Book Description
Christian Küchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees.
Publisher: Springer Science & Business Media
ISBN: 3834893994
Category : Mathematics
Languages : en
Pages : 178
Book Description
Christian Küchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees.
Stochastic Linear Programming Algorithms
Author: Janos Mayer
Publisher: Taylor & Francis
ISBN: 1351413694
Category : Computers
Languages : en
Pages : 164
Book Description
A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.
Publisher: Taylor & Francis
ISBN: 1351413694
Category : Computers
Languages : en
Pages : 164
Book Description
A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.
Risk Management in Stochastic Integer Programming
Author: Frederike Neise
Publisher: Springer Science & Business Media
ISBN: 3834895369
Category : Mathematics
Languages : en
Pages : 107
Book Description
The author presents two concepts to handle the classic linear mixed-integer two-stage stochastic optimization problem. She describes mean-risk modeling and stochastic programming with first order dominance constraints. Both approaches are applied to optimize the operation of a dispersed generation system.
Publisher: Springer Science & Business Media
ISBN: 3834895369
Category : Mathematics
Languages : en
Pages : 107
Book Description
The author presents two concepts to handle the classic linear mixed-integer two-stage stochastic optimization problem. She describes mean-risk modeling and stochastic programming with first order dominance constraints. Both approaches are applied to optimize the operation of a dispersed generation system.
Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming
Author: Uwe Gotzes
Publisher: Vieweg+Teubner Verlag
ISBN: 9783834808431
Category : Computers
Languages : en
Pages : 104
Book Description
Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. He illustrates the superiority of the proposed decomposition method over standard solvers for example with numerical experiments with instances from energy investment.
Publisher: Vieweg+Teubner Verlag
ISBN: 9783834808431
Category : Computers
Languages : en
Pages : 104
Book Description
Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. He illustrates the superiority of the proposed decomposition method over standard solvers for example with numerical experiments with instances from energy investment.
Applications of Stochastic Programming
Author: Stein W. Wallace
Publisher: SIAM
ISBN: 0898715555
Category : Mathematics
Languages : en
Pages : 701
Book Description
Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
Publisher: SIAM
ISBN: 0898715555
Category : Mathematics
Languages : en
Pages : 701
Book Description
Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
Stochastic Two-Stage Programming
Author: Karl Frauendorfer
Publisher: Springer Science & Business Media
ISBN: 3642956963
Category : Business & Economics
Languages : en
Pages : 236
Book Description
Stochastic Programming offers models and methods for decision problems wheresome of the data are uncertain. These models have features and structural properties which are preferably exploited by SP methods within the solution process. This work contributes to the methodology for two-stagemodels. In these models the objective function is given as an integral, whose integrand depends on a random vector, on its probability measure and on a decision. The main results of this work have been derived with the intention to ease these difficulties: After investigating duality relations for convex optimization problems with supply/demand and prices being treated as parameters, a stability criterion is stated and proves subdifferentiability of the value function. This criterion is employed for proving the existence of bilinear functions, which minorize/majorize the integrand. Additionally, these minorants/majorants support the integrand on generalized barycenters of simplicial faces of specially shaped polytopes and amount to an approach which is denoted barycentric approximation scheme.
Publisher: Springer Science & Business Media
ISBN: 3642956963
Category : Business & Economics
Languages : en
Pages : 236
Book Description
Stochastic Programming offers models and methods for decision problems wheresome of the data are uncertain. These models have features and structural properties which are preferably exploited by SP methods within the solution process. This work contributes to the methodology for two-stagemodels. In these models the objective function is given as an integral, whose integrand depends on a random vector, on its probability measure and on a decision. The main results of this work have been derived with the intention to ease these difficulties: After investigating duality relations for convex optimization problems with supply/demand and prices being treated as parameters, a stability criterion is stated and proves subdifferentiability of the value function. This criterion is employed for proving the existence of bilinear functions, which minorize/majorize the integrand. Additionally, these minorants/majorants support the integrand on generalized barycenters of simplicial faces of specially shaped polytopes and amount to an approach which is denoted barycentric approximation scheme.
Computational Stochastic Programming
Author: Lewis Ntaimo
Publisher: Springer Nature
ISBN: 3031524640
Category :
Languages : en
Pages : 518
Book Description
Publisher: Springer Nature
ISBN: 3031524640
Category :
Languages : en
Pages : 518
Book Description
A Primal-dual Decomposition-based Interior Point Approach to Two-stage Stochastic Linear Programming
Author: Arjan Bastiaan Berkelaar
Publisher:
ISBN: 9789050863728
Category :
Languages : en
Pages : 22
Book Description
Publisher:
ISBN: 9789050863728
Category :
Languages : en
Pages : 22
Book Description