Global and Dynamic Optimization using the Artificial Chemical Process Paradigm and Fast Monte Carlo Methods for the Solution of Population Balance Models

Irizarry, Roberto

doi:10.5772/14951

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Fundamentals Of Bacterial Colony Chemotaxis Algorithm1

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2013

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“…There are several variants and applications relative to BCC can be found in the literature (Li et al 2009;Li and Li 2012;Sun et al 2012;Lu et al 2013;Irizarry 2011). The basic steps of BCC are as follows (Lu et al 2013;Müller et al 2002;Sun et al 2012):…”

Section: Fundamentals Of Bacterial Colony Chemotaxis Algorithmmentioning

confidence: 99%

Bacteria Inspired Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, we present a set of algorithms that are inspired by the different bacteria behavioural patterns, i.e., bacterial foraging algorithm (BFA), bacterial colony chemotaxis (BCC) algorithm, superbug algorithm (SuA), bacterial colony optimization (BCO) algorithm, and viral system (VS) algorithm. We first describe the general knowledge of bacteria foraging behaviour in Sect. 2.1. Then, the fundamentals and performances of BFA, BCC algorithm, SuA, BCO algorithm, and VS algorithm are introduced in Sects. 2.2 and 2.3, respectively. Finally, Sect. 2.4 summarises this chapter.

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Section: Fundamentals Of Bacterial Colony Chemotaxis Algorithmmentioning

confidence: 99%

Bacteria Inspired Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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Emerging Chemistry-based CI Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, a set of emerging chemistry-based computational intelligence (CI) algorithms are introduced. We first, in Sect. 26.1, describe the organizational structure of this chapter. Then, from Sect. 26.2 to Sect. 26.5, each section is dedicated to a specific algorithm which falls within this category. The fundamentals of each algorithm and their corresponding performances compared with other CI algorithms can be found in each associated section. Finally, the conclusions drawn in Sect. 26.6 closes this chapter.

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Global and Dynamic Optimization using the Artificial Chemical Process Paradigm and Fast Monte Carlo Methods for the Solution of Population Balance Models

Cited by 2 publications

References 51 publications

Bacteria Inspired Algorithms

Bacteria Inspired Algorithms

Emerging Chemistry-based CI Algorithms

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