Influence of Ant Colony Optimization Parameters on the Algorithm Performance View Full Text


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Chapter Info

DATE

2018-01-03

AUTHORS

Stefka Fidanova , Olympia Roeva

ABSTRACT

In this paper an Ant Colony Optimization (ACO) algorithm for parameter identification of cultivation process models is proposed. In computational point of view it is a hard problem. To be solved problem with a high accuracy in reasonable time, metaheuristic techniques are used. The influence of ACO algorithm parameters, namely number of agents (ants) and number of iterations, to the quality of achieved solution is investigated. As a case study an E. coli fed-batch cultivation process is explored. Based on the parameter identification of E. coli MC4110 cultivation process model some conclusions for the optimal ACO parameter settings are done. More... »

PAGES

358-365

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-73441-5_38

DOI

http://dx.doi.org/10.1007/978-3-319-73441-5_38

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100171481


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