Ordering samples along environmental gradients using particle swarm optimization

Steven Essinger; Robi Polikar; Gail Rosen

doi:10.1109/IEMBS.2011.6091087

Ordering samples along environmental gradients using particle swarm optimization

Steven Essinger, Robi Polikar Gail Rosen

Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2011, pp 4382-4385

2011

: https://doi.org/10.1109/IEMBS.2011.6091087

: 22255310

Models, Theoretical

Algorithms

Due to the enormity of the solution space for sequential ordering problems, non-exhaustive heuristic techniques have been the focus of many research efforts, particularly in the field of operations research. In this paper, we outline an ecologically motivated problem in which environmental samples have been obtained along a gradient (e.g. pH), with which we desire to recover the sample order. Not only do we model the problem for the benefit of an optimization approach, we also incorporate hybrid particle swarm techniques to address the problem. The described method is implemented on a real dataset from which 22 biological samples were obtained along a pH gradient. We show that we are able to approach the optimal permutation of samples by evaluating only approximately 5000 solutions--infinitesimally smaller than the 22! possible solutions.

: Ordering samples along environmental gradients using particle swarm optimization
: Steven Essinger - Drexel University
Robi Polikar - Drexel University
Gail Rosen - Drexel University
: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2011, pp 4382-4385
: The Institute of Electrical and Electronics Engineers, Inc. (IEEE); United States
: Conference proceeding
: English
: Electrical and Computer Engineering
: WOS:000298810003179
: 2-s2.0-84863602655
: 1424441226; 1457715899; 9781457715891; 9781424441228; 991014877915404721

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esploro.research.conf.research.portal.label.prefix.inciteWOSResearchAreas: Engineering, Biomedical; Engineering, Electrical & Electronic