Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications

By Swagatam Das, Arijit Biswas, Sambarta Dasgupta, Ajith Abraham. IEEE Symposium on Foundations of Computational Intelligence, 2009

512 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/203efcbf0e78bac42528dfc338bf657f699fb536

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Gaurav Dhiman
2. Vijay Kumar
3. Afeez Abidemi
4. Emmanuel Gbenga Dada
5. Patrick Siarry
6. Ban Mohammed Khammas
7. Ilhem Boussaïd
8. Nitin Mittal

In Genetics

1. Afeez Abidemi
2. Emmanuel Gbenga Dada
3. Vijay Kumar
4. Patrick Siarry
5. Ban Mohammed Khammas
6. Ilhem Boussaïd
7. Arpan Kumar Kar
8. Julien Lepagnot

In Molecular Biology

1. Vijay Kumar
2. Patrick Siarry
3. Ilhem Boussaïd
4. Arpan Kumar Kar
5. Julien Lepagnot
6. Gaurav Dhiman

Citations in the corpus

• New inspirations in swarm intelligence: a survey (2011, unknown): “Some other applications are summarised in Das et al. (2009).”
• Modified Grey Wolf Optimizer for Global Engineering Optimization (2016, methodology): “The major algorithms in this field include Artificial Immune Systems (AIS) [34], Bacterial ForagingOptimization (BFO) [35], and Krill Herd Algorithm [36].”
• A survey on optimization metaheuristics (2013, methodology): “In [62], the authors discussed some variations on the original BFOA algorithm and hybridizations of BFOA with other optimization techniques.”
• Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems (2019, methodology): “Emperor Penguin Optimizer [41] EPO Collective Neurodynamic Optimization [1,42–44] CNO Artificial Chemical Reaction Optimization Algorithm [45] ACROA Galaxy-based Search Algorithm [46] GbSA Firefly Algorithm [47] FA Exchange Market Algorithm [48] EMA Social-Based Algorithm [49] SBA Harmony Search [50”
• Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems (2022, background): “Specifics on these processes, as well as the BFO implementation steps, can be found in Das et al. (2009); Datta and Nandakumar (2017); Jhankal and Adhyaru (2011).”
• Bio inspired computing - A review of algorithms and scope of applications (2016, methodology): “This algorithm could be efficiently used to find potential suitable solutions by the application of operators like chemotaxis, swarming, reproduction, and elimination-dispersal (Biswas, A. et al, 2007; Das et al., 2009).”