Column Generation (63 results)

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Condition: Gebraucht / Used. 2008. Pap. vi,157pp. 8°. Diss./Thesis. Blibliogr.

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2020 in the subject Business economics - Operations Research, grade: 1,3, University of Kaiserslautern, language: English, abstract: The Cutting Stock Problem (CSP) appears when a material has to be cut into smaller pieces and occurs in many branches of industry. On the one hand, the CSP belongs to the earliest studied problems through methods of Operational Research and on the other to the most intensively studied problems in combinatorial optimization.In the one-dimensional Cutting Stock Problem (1DCSP), there are typically identical pieces of a single standard length, called rolls, that need to be cut into smaller pieces lengthwise. Examples, where the cutting process is performed in one single dimension, can be found in the steel industry and the paper industry . The two-dimensional CSP (2DCSP) is classified into cutting of regular and irregular shapes and is often found in clothing and shoe-leather industries. A real-world application of a three-dimensional CSP (3DCSP) lies in the production of mattresses, where rubber blocks are cut into different types of orthogonal rectangular prisms. Methods of finding an optimal solution exist for the 1DCSP. Often in large problem instances, the required time for finding an optimal solution proliferates, and heuristics may turn out to be the more sensible option in this case. Nowadays, there are countless different ways to find acceptable solutions in a fast manner of time, among others, the column generation approach, which is the central component of the present work.This work is organized as follows. In Chapter 2, a brief overview of different formulations for the CSP is given. Furthermore, some known extensions of the classic CSP are presented, e.g., raw material, that consists of various sizes at the same time. CSP has many relatives, the closest is the Bin Packing Problem (BPP), where items are packed into bins as efficiently as possible. The third chapter shows the column generation technique for solving the CSP and provides the connection between a solution for the relaxed problem and an integer solution. In Chapter 4, different test instances of the CSP are compared using a column generation implementation solved in three different MIP solvers. The conclusion is provided in Chapter 5.…

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Taschenbuch. Condition: Neu. A Column Generation Approach For Stochastic Optimization Problems | In the applications of a stochastic generalized assignment problem and a shift planning and scheduling problem with uncertain demand | Yong Min Wang | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639006421 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.…

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Paperback. Condition: Good. Column Generation is an insightful overview of the state of the art in integer programming column generation and its many applications. The volume begins with "A Primer in Column Generation" which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on "Shortest Path Problems with Resource Constraints," "Vehicle Routing Problem with Time Window," "Branch-and-Price Heuristics," "Cutting Stock Problems," each dealing with methodological aspects of the field. Three chapters deal with transportation applications: "Large-scale Models in the Airline Industry," "Robust Inventory Ship Routing by Column Generation," and "Ship Scheduling with Recurring Visits and Visit Separation Requirements." Production is the focus of another three chapters: "Combining Column Generation and Lagrangian Relaxation," "Dantzig-Wolfe Decomposition for Job Shop Scheduling," and "Applying Column Generation to Machine Scheduling." The final chapter by François Vanderbeck, "Implementing Mixed Integer Column Generation," reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).…

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Taschenbuch. Condition: Neu. Column Generation | Guy Desaulniers (u. a.) | Taschenbuch | xv | Englisch | 2010 | Springer | EAN 9781441937995 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Column Generation is an insightful overview of the state of the art in integer programming column generation and its many applications. The volume begins with 'A Primer in Column Generation' which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on 'Shortest Path Problems with Resource Constraints,' 'Vehicle Routing Problem with Time Window,' 'Branch-and-Price Heuristics,' 'Cutting Stock Problems,' each dealing with methodological aspects of the field. Three chapters deal with transportation applications: 'Large-scale Models in the Airline Industry,' 'Robust Inventory Ship Routing by Column Generation,' and 'Ship Scheduling with Recurring Visits and Visit Separation Requirements.' Production is the focus of another three chapters: 'Combining Column Generation and Lagrangian Relaxation,' 'Dantzig-Wolfe Decomposition for Job Shop Scheduling,' and 'Applying Column Generation to Machine Scheduling.' The final chapter by François Vanderbeck, 'Implementing Mixed Integer Column Generation,' reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).…

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