Friday, September 20, 2019 - 11:00 to 12:30
SCHOOL OF COMPUTER SCIENCE
The School of Computer Science at the University of Windsor is pleased to present …
MSc Thesis Defense by:
Ramya Ravichandran
Date: Friday September 20, 2019
Time: 11:00am-12:30pm
Location: Essex Hall Room 122
Abstract:
Decomposition is used to solve optimization problems by introducing many simple scalar optimization subproblems and optimizing them simultaneously. Dynamic Multi-Objective Optimization Problems (DMOP) have several objective functions and constraints that vary over time. As a consequence of such dynamic changes, the optimal solutions may vary over time, affecting the performance of convergence. In this thesis, we propose a new Cultural Algorithm (CA) based on decomposition (CA/D). The objective of the CA/D algorithm is to decompose DMOP into a number of subproblems that can be optimized using the information shared by neighboring problems. The proposed CA/D approach is evaluated using a number of CEC 2015 optimization benchmark functions. When compared to CA, Multi-population CA (MPCA), and MPCA incorporating game strategies (MPCA-GS), the results obtained showed that CA/D outperformed them in 7 out of the 15 benchmark functions.
Thesis Committee:
Internal Reader: Dr. Saeed Samet
External Reader: Dr. Kemal Tepe
Advisor: Dr. Ziad Kobti
Chair: Dr. Jinguao Lu
Thesis Defense Announcement
5113 Lambton Tower, 401 Sunset Ave., Windsor ON, N9B 3P4, (519) 253-3000 Ext. 3716 csgradinfo@uwindsor.ca
(519)253-3000