Abstract
In this chapter, we discuss the parallel implementation of the GOP algorithm, as studied by Androulakis et al. (1996), and we present distributed computing results for indefinite quadratic programming problems and for large-scale pooling problems that arise in chemical refineries. Section 7.1 focuses on the critical components of the distributed implementation of the GOP approach. Section 7.2 presents the computational results for large-scale indefinite quadratic problems. Finally, section 7.3 discusses the computational performance of the parallel GOP approach for large-scale blending and pooling problems.
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© 2000 Springer Science+Business Media Dordrecht
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Floudas, C.A. (2000). The GOP Approach : Distributed Implementation. In: Deterministic Global Optimization. Nonconvex Optimization and Its Applications, vol 37. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4949-6_7
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DOI: https://doi.org/10.1007/978-1-4757-4949-6_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4820-5
Online ISBN: 978-1-4757-4949-6
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