Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Videos
Videos
Thesis submission
Thesis submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Contact us
Contact us
Multi-objective feasibility enhanced particle swarm optimization
Date
2018-12-02
Author
Hasanoglu, Mehmet Sinan
Dölen, Melik
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
16
views
0
downloads
Cite This
This article introduces a new method entitled multi-objective feasibility enhanced partical swarm optimization (MOFEPSO), to handle highly-constrained multi-objective optimization problems. MOFEPSO, which is based on the particle swarm optimization technique, employs repositories of non-dominated and feasible positions (or solutions) to guide feasible particle flight. Unlike its counterparts, MOFEPSO does not require any feasible solutions in the initialized swarm. Additionally, objective functions are not assessed for infeasible particles. Such particles can only fly along sensitive directions, and particles are not allowed to move to a position where any previously satisfied constraints become violated. These unique features help MOFEPSO gradually increase the overall feasibility of the swarm and to finally attain the optimal solution. In this study, multi-objective versions of a classical gear-train optimization problem are also described. For the given problems, the article comparatively evaluates the performance of MOFEPSO against several popular optimization algorithms found in the literature.
Subject Keywords
Management Science and Operations Research
,
Industrial and Manufacturing Engineering
,
Control and Optimization
,
Applied Mathematics
,
Computer Science Applications
URI
https://hdl.handle.net/11511/42570
Journal
ENGINEERING OPTIMIZATION
DOI
https://doi.org/10.1080/0305215x.2018.1431232
Collections
Department of Mechanical Engineering, Article
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. S. Hasanoglu and M. Dölen, “Multi-objective feasibility enhanced particle swarm optimization,”
ENGINEERING OPTIMIZATION
, vol. 50, no. 12, pp. 2013–2037, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42570.