Pomitaxis: Computing with a bacterial-inspired algorithm
We present a general-purpose optimisation algorithm inspired by "run-and-tumble2, the biased random chemotactic swimming strategy used by the bacterium E coli to locate regions of high nutrient concentration. The method uses particles (corresponding to bacteria) that swim through the variable...
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| Format: | Conference item |
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2007
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| _version_ | 1797053603102326784 |
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| author | Nicolau, D Maini, P |
| author_facet | Nicolau, D Maini, P |
| author_sort | Nicolau, D |
| collection | OXFORD |
| description | We present a general-purpose optimisation algorithm inspired by "run-and-tumble2, the biased random chemotactic swimming strategy used by the bacterium E coli to locate regions of high nutrient concentration. The method uses particles (corresponding to bacteria) that swim through the variable space (corresponding to the attractant concentration profile). By constantly performing temporal comparisons, the particles drift towards the minimum or maximum of the function of interest. We illustrate the use of our method with three simple examples. We also present a discrete version of the algorithm. The new algorithm is expected to be useful in combinatorial optimisation problems involving many variables, where the functional landscape is apparently stochastic and has local minima, but preserves some derivative structure at the mesoscale. |
| first_indexed | 2024-03-06T18:45:58Z |
| format | Conference item |
| id | oxford-uuid:0e851148-ec1b-4c8e-8f33-81d407c00dcf |
| institution | University of Oxford |
| last_indexed | 2024-03-06T18:45:58Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:0e851148-ec1b-4c8e-8f33-81d407c00dcf2022-03-26T09:46:26ZPomitaxis: Computing with a bacterial-inspired algorithmConference itemhttp://purl.org/coar/resource_type/c_5794uuid:0e851148-ec1b-4c8e-8f33-81d407c00dcfMathematical Institute - ePrints2007Nicolau, DMaini, PWe present a general-purpose optimisation algorithm inspired by "run-and-tumble2, the biased random chemotactic swimming strategy used by the bacterium E coli to locate regions of high nutrient concentration. The method uses particles (corresponding to bacteria) that swim through the variable space (corresponding to the attractant concentration profile). By constantly performing temporal comparisons, the particles drift towards the minimum or maximum of the function of interest. We illustrate the use of our method with three simple examples. We also present a discrete version of the algorithm. The new algorithm is expected to be useful in combinatorial optimisation problems involving many variables, where the functional landscape is apparently stochastic and has local minima, but preserves some derivative structure at the mesoscale. |
| spellingShingle | Nicolau, D Maini, P Pomitaxis: Computing with a bacterial-inspired algorithm |
| title | Pomitaxis: Computing with a bacterial-inspired algorithm |
| title_full | Pomitaxis: Computing with a bacterial-inspired algorithm |
| title_fullStr | Pomitaxis: Computing with a bacterial-inspired algorithm |
| title_full_unstemmed | Pomitaxis: Computing with a bacterial-inspired algorithm |
| title_short | Pomitaxis: Computing with a bacterial-inspired algorithm |
| title_sort | pomitaxis computing with a bacterial inspired algorithm |
| work_keys_str_mv | AT nicolaud pomitaxiscomputingwithabacterialinspiredalgorithm AT mainip pomitaxiscomputingwithabacterialinspiredalgorithm |