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Feasibility enhanced particle swarm optimization for constrained mechanical design problems
Date
2018-01-01
Author
Hasanoglu, Mehmet Sinan
Dölen, Melik
Metadata
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Constrained optimization problems constitute an important fraction of optimization problems in the mechanical engineering domain. It is not uncommon for these problems to be highly-constrained where a specialized approach that aims to improve constraint satisfaction level of the whole population as well as finding the optimum is deemed useful especially when the objective functions are very costly. A new algorithm called Feasibility Enhanced Particle Swarm Optimization (FEPSO), which treats feasible and infeasible particles differently, is introduced. Infeasible particles in FEPSO do not need to evaluate objective functions and fly only based on social attraction depending on a single violated constraint, called the activated constraint, which is selected at each iteration based on constraint priorities and flight occurs only along dimensions of the search space to which the activated constraint is sensitive. To ensure progressive improvement of constraint satisfaction, particles are not allowed to violate a satisfied constraint in FEPSO. The highly-constrained four-stage gear train problem and its two variants introduced in this paper are used to assess the effectiveness of FEPSO. The results suggest that FEPSO is effective and consistent in obtaining feasible points, finding good solutions, and improving the constraint satisfaction level of the swarm as a whole.
Subject Keywords
Mechanical Engineering
URI
https://hdl.handle.net/11511/34535
Journal
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
DOI
https://doi.org/10.1177/0954406216681593
Collections
Department of Mechanical Engineering, Article
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M. S. Hasanoglu and M. Dölen, “Feasibility enhanced particle swarm optimization for constrained mechanical design problems,”
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
, pp. 381–400, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34535.