Abstract
In this chapter, the background of the methods and tools used in the development and implementation of the different mathematical models and solution approaches devised in this book is described. Mathematical programming constitutes the main optimization approach for dealing with the several industrial case studies considered. First, some general principles of mathematical programming are discussed. Afterwards, some theoretical concepts and solution techniques for linear and mixed integer programming problems are briefly presented. Finally, a short description of the commercial tools utilized to solve the problems under study is given.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Castillo E, Conejo AJ et al (2001) Building and solving mathematical programming models in engineering and science. Wiley, New York, USA
Conejo AJ, Nogales FJ, Prieto FJ (2002) A decomposition procedure based on approximate Newton directions. Math Program 93(3):495–515
Dantzig GB, Thapa MN (1997) Linear programming 1: introduction. Series in operations research. Springer-Verlag New York, Inc., USA
Dantzig GB, Thapa MN. (2003) Linear programming 2: theory and extensions. Series in operations research. Springer-Verlag New York, Inc., USA
Duran M, Grossmann IE (1986) An outer-approximation algorithm for a class of mixed integer nonlinear programs. Math Progr 36:307–339
Ferris, M. MATLAB and GAMS (1999): Interfacing optimization and visualization software. Technical report, University of Wisconsin
Gass SI (2003) Linear programming: methods and applications. Dover Publications, Inc., Mineola, New York, USA
Land AH, Doig AG (1960) An automatic method for solving discrete programming problems. Econometrica 28:497–520
Lee S, Grossmann IE (2000) New algorithms for nonlinear disjunctive programming. Comput Chem Eng 24:2125–2141
Nemhauser G, Wolsey LA (1999) Integer and combinatorial optimization. series in discrete mathematics and optimization. Wiley-Interscience, Wiley-Interscience, New York, USA
Raman R, Grossmann IE (1994) Modeling and computational techniques for logic based integer programming. Comput Chem Eng 18:563–578
Rosenthal RE (2010) GAMS—a user’s guide. GAMS Development Corporation, Washington, DC, USA
The Mathworks, Inc. MATLAB (1998) The language of technical computing: MATLAB notebook user’s guide. The Mathworks Inc., Natick, MA, USA
Wolsey LA (1998) Integer programming. Series in discrete mathematics and optimization. Wiley-Interscience, NewYork, USA
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kopanos, G.M., Puigjaner, L. (2019). Methods and Tools. In: Solving Large-Scale Production Scheduling and Planning in the Process Industries. Springer, Cham. https://doi.org/10.1007/978-3-030-01183-3_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-01183-3_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01182-6
Online ISBN: 978-3-030-01183-3
eBook Packages: EngineeringEngineering (R0)