Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52599
Title: Constrained differential evolution optimization for underwater glider path planning in sub-mesoscale eddy sampling
Authors: Zamuda, Aleš
Hernández Sosa, José Daniel 
Adler, Leonhard
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Constraint handling
Differential evolution
Sub-mesoscale ocean eddy sampling
Underwater glider path planning
Underwater robotics
Issue Date: 2016
Journal: Applied Soft Computing Journal 
Abstract: This paper presents an approach for tackling constrained underwater glider path planning (UGPP), where the feasible path area is defined as a corridor around the border of an ocean eddy. The objective of the glider here is to sample the oceanographic variables more efficiently while keeping a bounded trajectory. Therefore, we propose a solution based on differential evolution (DE) algorithm mechanisms, including in its configuration self-adaptation of control parameters, population size reduction, ε-constraint handling with adjustment, and mutation based on elitistic best vector. Different aspects of this DE configuration are studied for the constrained UGPP challenge, on a prepared benchmark set comprised of 28 different specialized scenarios. The DE configurations were tested over a benchmark set over 51 independent runs for each DE configuration aspect. Comparison and suitability for the combination of these mechanisms is reported, through the per-scenario and aggregated statistical performance differences, including different constraint handling definition strategies, different DE mutation strategies' configurations, and population sizing parameterizations. Our proposed solution outranked all other compared algorithms, keeping a trajectory within the limits with 100% success rate in all physically feasible scenarios; on average, it improved the randomly initialized trajectories fitness by roughly 50%, even reaching perfect fitness (all-around, 360-degree eddy corridor sampling) in some scenarios.
URI: http://hdl.handle.net/10553/52599
ISSN: 1568-4946
DOI: 10.1016/j.asoc.2016.01.038
Source: Applied Soft Computing Journal[ISSN 1568-4946],v. 42, p. 93-118
Appears in Collections:Artículos
Show full item record

SCOPUSTM   
Citations

42
checked on Aug 1, 2021

WEB OF SCIENCETM
Citations

38
checked on Aug 1, 2021

Page view(s)

7
checked on Jul 24, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.