A Multi-stage Stochastic Programming Approach for Production Planning with Uncertainty in the Quality of Raw Materials and Demand

A Multi-stage Stochastic Programming Approach for Production Planning with Uncertainty in the Quality of Raw Materials and Demand PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand

A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand PDF Author:
Publisher:
ISBN:
Category :
Languages : fr
Pages : 22

Get Book Here

Book Description


Stochastic Programming

Stochastic Programming PDF Author: Horand Gassmann
Publisher: World Scientific
ISBN: 9814407518
Category : Business & Economics
Languages : en
Pages : 549

Get Book Here

Book Description
This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems.

A Stochastic Programming Approach for Production Planning with Uncertainty in the Quality of Raw Materials

A Stochastic Programming Approach for Production Planning with Uncertainty in the Quality of Raw Materials PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


A stochastic programming approach for production planning with uncertainty in the quality of raw materials : a case in sawmills

A stochastic programming approach for production planning with uncertainty in the quality of raw materials : a case in sawmills PDF Author:
Publisher:
ISBN:
Category :
Languages : fr
Pages : 20

Get Book Here

Book Description


Dynamic lot sizing problems with stochastic production output

Dynamic lot sizing problems with stochastic production output PDF Author: Michael Kirste
Publisher: BoD – Books on Demand
ISBN: 3744838056
Category : Business & Economics
Languages : en
Pages : 250

Get Book Here

Book Description
In the real world, production systems are affected by external and internal uncertainties. Stochastic demand - an external uncertainty - arises mainly due to forecast errors and unknown behavior of customers in future. Internal uncertainties occur in situations where random yield, random production capacity, or stochastic processing times affect the productivity of a manufacturing system. The resulting stochastic production output is especially present in industries with modern and complex technologies as the semiconductor industry. This thesis provides model formulations and solution methods for capacitated dynamic lot sizing problems with stochastic demand and stochastic production output that can be used by practitioners within Manufacturing Resource Planning Systems (MRP), Capacitated Production Planning Systems (CPPS), and Advanced Planning Systems (APS). In all models, backordered demand is controlled with service levels. Numerical studies compare the solution methods and give managerial implications in presence of stochastic production output. This book addresses practitioners, consultants, and developers as well as students, lecturers, and researchers with focus on lot sizing, production planning, and supply chain management.

Multiphysics Modelling and Simulation for Systems Design and Monitoring

Multiphysics Modelling and Simulation for Systems Design and Monitoring PDF Author: Mohamed Haddar
Publisher: Springer
ISBN: 3319145320
Category : Technology & Engineering
Languages : en
Pages : 551

Get Book Here

Book Description
This book reports on the state of the art in the field of multiphysics systems. It consists of accurately reviewed contributions to the MMSSD’2014 conference, which was held from December 17 to 19, 2004 in Hammamet, Tunisia. The different chapters, covering new theories, methods and a number of case studies, provide readers with an up-to-date picture of multiphysics modeling and simulation. They highlight the role played by high-performance computing and newly available software in promoting the study of multiphysics coupling effects, and show how these technologies can be practically implemented to bring about significant improvements in the field of design, control and monitoring of machines. In addition to providing a detailed description of the methods and their applications, the book also identifies new research issues, challenges and opportunities, thus providing researchers and practitioners with both technical information to support their daily work and a new source of inspiration for their future research.

Nonlinear Interval Optimization for Uncertain Problems

Nonlinear Interval Optimization for Uncertain Problems PDF Author: Chao Jiang
Publisher: Springer Nature
ISBN: 9811585466
Category : Mathematics
Languages : en
Pages : 291

Get Book Here

Book Description
This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.

Multi-stage Stochastic Programming Models in Production Planning

Multi-stage Stochastic Programming Models in Production Planning PDF Author: Kai Huang
Publisher:
ISBN:
Category : Approximation theory
Languages : en
Pages :

Get Book Here

Book Description
In this thesis, we study a series of closely related multi-stage stochastic programming models in production planning, from both a modeling and an algorithmic point of view. We first consider a very simple multi-stage stochastic lot-sizing problem, involving a single item with no fixed charge and capacity constraint. Although a multi-stage stochastic integer program, this problem can be shown to have a totally unimodular constraint matrix. We develop primal and dual algorithms by exploiting the problem structure. Both algorithms are strongly polynomial, and therefore much more efficient than the Simplex method. Next, motivated by applications in semiconductor tool planning, we develop a general capacity planning problem under uncertainty. Using a scenario tree to model the evolution of the uncertainties, we present a multi-stage stochastic integer programming formulation for the problem. In contrast to earlier two-stage approaches, the multi-stage model allows for revision of the capacity expansion plan as more information regarding the uncertainties is revealed. We provide analytical bounds for the value of multi-stage stochastic programming over the two-stage approach. By exploiting the special simple stochastic lot-sizing substructure inherent in the problem, we design an efficient approximation scheme and show that the proposed scheme is asymptotically optimal. We conduct a computational study with respect to a semiconductor-tool-planning problem. Numerical results indicate that even an approximate solution to the multi-stage model is far superior to any optimal solution to the two-stage model. These results show that the value of multi-stage stochastic programming for this class of problem is extremely high. Next, we extend the simple stochastic lot-sizing model to an infinite horizon problem to study the planning horizon of this problem. We show that an optimal solution of the infinite horizon problem can be approximated by optimal solutions of a series of finite horizon problems, which implies the existence of a planning horizon. We also provide a useful upper bound for the planning horizon.

Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics

Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics PDF Author: Vasant, Pandian
Publisher: IGI Global
ISBN: 1466696451
Category : Mathematics
Languages : en
Pages : 999

Get Book Here

Book Description
Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems. The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems. .