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12 - Solution Methods: Sequential Environments

from Part IV - Special Topics

Published online by Cambridge University Press:  01 May 2021

Christos T. Maravelias
Christos T. Maravelias
Affiliation:
Princeton University, New Jersey
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Summary

The goal of the present chapter, as well as Chapter 13, is to illustrate how problem features can be exploited to develop more efficient models and/or specialized algorithms. We start, in the present chapter, with solution methods for problems in sequential environments. Specifically, we discuss four methods: (1) a decomposition approach, in Section 12.1; (2) preprocessing algorithms and tightening constraints, in Section 12.2; (3) a reformulation and tightening constraints based on time windows, in Section 12.3; and (4) a two-step algorithm, combining the advantages of discrete and continuous time models, in Section 12.4. While all presented methods can be applied to a wide range of problems, we present them for a subset of problems for the sake of brevity. Also, all methods can be applied to problems under different processing features, but to keep the presentation simple, we discuss problems with no shared utilities and no storage constraints.

Keywords

Decompositiontighteningpreprocessingvalid inequalitiestightening constraintshybrid methodsdiscrete-continuous algorithm
Type
Chapter
Information
Chemical Production Scheduling
Mixed-Integer Programming Models and Methods
 , pp. 289 - 317
Publisher: Cambridge University Press
Print publication year: 2021

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