Optimization with Disjunctive Constraints
Optimization with Disjunctive Constraints

Author: H.D. Sherali

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 168

ISBN-13: 3642487947

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The disjunctive cut principle of Balas and Jeroslow, and the related polyhedral annexation principle of Glover, provide new insights into cutting plane theory. This has resulted in its ability to not only subsume many known valid cuts but also improve upon them. Originally a set of notes were written for the purpose of putting together in a common terminology and framework significant results of Glover and others using a geometric approach, referred to in the literature as convexity cuts, and the algebraic approach of Balas and Jeroslow known as Disjunctive cuts. As it turned out subsequently the polyhedral annexation approach of Glover is also closely connected with the basic disjunctive principle of Balas and Jeroslow. In this monograph we have included these results and have also added several published results which seem to be of strong interest to researchers in the area of developing strong cuts for disjunctive programs. In particular, several results due to Balas [4,5,6,7], Glover [18,19] and Jeroslow [23,25,26] have been used in this monograph. The appropriate theorems are given without proof. The notes also include several results yet to be published [32,34,35] obtained under a research contract with the National Science Foundation to investigate solution methods for disjunctive programs. The monograph is self-contained and complete in the sense that it attempts to pool together existing results which the authors viewed as important to future research on optimization using the disjunctive cut approach.

Disjunctive Programming
Disjunctive Programming

Author: Egon Balas

Publisher: Springer

Published: 2018-11-27

Total Pages: 238

ISBN-13: 3030001482

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Disjunctive Programming is a technique and a discipline initiated by the author in the early 1970's, which has become a central tool for solving nonconvex optimization problems like pure or mixed integer programs, through convexification (cutting plane) procedures combined with enumeration. It has played a major role in the revolution in the state of the art of Integer Programming that took place roughly during the period 1990-2010. The main benefit that the reader may acquire from reading this book is a deeper understanding of the theoretical underpinnings and of the applications potential of disjunctive programming, which range from more efficient problem formulation to enhanced modeling capability and improved solution methods for integer and combinatorial optimization. Egon Balas is University Professor and Lord Professor of Operations Research at Carnegie Mellon University's Tepper School of Business.

Mixed Integer Nonlinear Programming
Mixed Integer Nonlinear Programming

Author: Jon Lee

Publisher: Springer Science & Business Media

Published: 2011-12-02

Total Pages: 687

ISBN-13: 1461419271

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Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.

Chemical Production Scheduling
Chemical Production Scheduling

Author: Christos T. Maravelias

Publisher: Cambridge University Press

Published: 2021-05-06

Total Pages: 459

ISBN-13: 1107154758

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Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners.

Pyomo – Optimization Modeling in Python
Pyomo – Optimization Modeling in Python

Author: William E. Hart

Publisher: Springer Science & Business Media

Published: 2012-02-15

Total Pages: 245

ISBN-13: 146143226X

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This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs.

Decision Diagrams for Optimization
Decision Diagrams for Optimization

Author: David Bergman

Publisher: Springer

Published: 2016-11-01

Total Pages: 262

ISBN-13: 3319428497

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This book introduces a novel approach to discrete optimization, providing both theoretical insights and algorithmic developments that lead to improvements over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques. The book will be useful for researchers and practitioners in discrete optimization and constraint programming. "Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world." [Pascal Van Hentenryck]

Constraint-Based Scheduling
Constraint-Based Scheduling

Author: Philippe Baptiste

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 204

ISBN-13: 1461514797

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Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsible for the "hardness" of the scheduling problem. Chapters 6, 7, and 8 are dedicated to the resolution of several scheduling problems. These examples illustrate the use and the practical efficiency of the constraint propagation methods of the previous chapters. They also show that besides constraint propagation, the exploration of the search space must be carefully designed, taking into account specific properties of the considered problem (e.g., dominance relations, symmetries, possible use of decomposition rules). Chapter 9 mentions various extensions of the model and presents promising research directions.