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Cultural Algorithm Based on Decomposition to Solve Optimization Problems

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Cultural Algorithm Based on Decomposition to Solve Optimization Problems University of Windsor Scholarship at UWindsor Electronic Theses and Dissertations Theses, Dissertations, and Major Papers 9-20-2019 Cultural Algorithm based on Decomposition to solve Optimization Problems Ramya Ravichandran University of Windsor Follow this and additional works at: https://scholar.uwindsor.ca/etd Recommended Citation Ravichandran, Ramya, "Cultural Algorithm based on Decomposition to solve Optimization Problems" (2019). Electronic Theses and Dissertations. 7835. https://scholar.uwindsor.ca/etd/7835 This online database contains the full-text of PhD dissertations and Masters’ theses of University of Windsor students from 1954 forward. These documents are made available for personal study and research purposes only, in accordance with the Canadian Copyright Act and the Creative Commons license—CC BY-NC-ND (Attribution, Non-Commercial, No Derivative Works). Under this license, works must always be attributed to the copyright holder (original author), cannot be used for any commercial purposes, and may not be altered. Any other use would require the permission of the copyright holder. Students may inquire about withdrawing their dissertation and/or thesis from this database. For additional inquiries, please contact the repository administrator via email ([email protected]) or by telephone at 519-253-3000ext. 3208. Cultural Algorithm based on Decomposition to solve Optimization Problems By Ramya Ravichandran A Thesis Submitted to the Faculty of Graduate Studies through the School of Computer Science in Partial Fulfillment of the Requirements for the Degree of Master of Science at the University of Windsor Windsor, Ontario, Canada 2019 © Ramya Ravichandran, 2019 Cultural Algorithm based on Decomposition to solve Optimization Problems By Ramya Ravichandran APPROVED BY: ______________________________________________ K. Tepe Department of Electrical and Computer Engineering ______________________________________________ S. Samet School of Computer Science ______________________________________________ Z. Kobti, Advisor School of Computer Science September 20th, 2019 DECLARATION OF CO-AUTHORSHIP / PREVIOUS PUBLICATION 1. Co-authorship I hereby declare that this thesis incorporates material that is the result of research conducted under the supervision of Dr. Ziad Kobti. In all cases, the key ideas, primary contribution, experimental designs, data analysis, and interpretation were performed by the author, and the contribution of the co- author was primarily through the proofreading of the published manuscripts. I am aware of the University of Windsor Senate Policy on Authorship, and I certify that I have properly acknowledged the contribution of other researchers to my thesis, and have obtained written permission from each of the co-author(s) to include the above material(s) in my thesis. I certify that, with the above qualification, this thesis, and the research to which it refers, is the product of my work. 2. Previous Publication This thesis includes one original paper that has been previously submitted for publication in peer-reviewed journals, as follows: iii Section Publication title/ Full citation Publication status 3, 4 Ramya Ravichandran and Ziad Kobti “ Accepted Solving Dynamic Multi-Objective Optimization Problem Using Cultural Algorithm based on Decomposition.” In 2019 International Symposium on Computing and Artificial Intelligence (ISCAI 2019), Vancouver, Canada. I certify that I have obtained a written permission from the copyright owner(s) to include the above published material(s) in my thesis. I certify that the above material describes work completed during my registration as a graduate student at the University of Windsor. 3. General I declare that, to the best of my knowledge, my thesis does not infringe upon anyone's copyright nor violate any propriety rights and that any ideas, techniques, quotations, or any other material from the work of other people included in my thesis, published or otherwise, are fully acknowledged in accordance with the standard referencing practices. Furthermore, to the extent iv that I have included copyright material that surpasses the bounds of fair dealing within the meaning of Canada Copyright Act, I certify that I have obtained written permission from the copyright owner to include such material in my thesis. I declare that this is a true copy of my thesis, including any final revisions, as approved by my thesis committee and the Graduate Studies Office, and that this thesis has not been submitted for a higher degree to any other University or Institution. v 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. vi DEDICATION I would like to dedicate this thesis to my family Father: Ravichandran Egappan Mother: Janagi Ravichandran Sister: Aishwarya Ravichandran vii ACKNOWLEDGMENTS There are many people I would like to thank for the successful completion of my master thesis. First and foremost, I would like to express my sincere gratitude to my supervisor, Dr. Ziad Kobti, for his continuous support of my research study, for his patience, motivation, enthusiasm, and immense knowledge. He helped me in accomplishing my goals and has provided valuable guidance in improving research skills. It was a great pleasure to work and discuss with him. I would also like to appreciate the time he dedicated for me and the funding he provided me to complete this thesis. Without his support, this thesis would not be complete. I would also like to thank my committee members – Dr. Tepe and Dr. Samet – whose inputs and suggestion have given a better shape to my research. I also would like to thank the support of Mrs. Melissa, Mrs.Christine, and Mrs. Gloria for helping with various academic issues. I am very thankful to my parents and friends who gave me the strength, moral support, and unconditional love, which kept me motivated to pursue my research. Last but not least, I would like to thank God for giving this excellent opportunity. viii TABLE OF CONTENTS DECLARATION OF CO-AUTHORSHIP / PREVIOUS PUBLICATION ... iii ABSTRACT .................................................................................................................... vi DEDICATION .............................................................................................................. vii ACKNOWLEDGMENTS ......................................................................................... viii LIST OF TABLES ........................................................................................................ xii LIST OF FIGURES .................................................................................................... xiii LIST OF ABBREVIATIONS .....................................................................................xv Chapter 1 ..........................................................................................................................1 Introduction ...................................................................................................................1 1.1 Background ..................................................................................................................... 1 1.2 Problem Definition ............................................................................................................. 3 1.2.1 Dynamic Multi-Objective Optimization .................................................................... 5 1.3 Evolutionary Computation ................................................................................................. 8 1.4 Decomposition ................................................................................................................... 11 1.5 Research Motivation.......................................................................................................... 12 1.6 Thesis Statement................................................................................................................ 13 1.7 Thesis Contribution ........................................................................................................... 14 1.8 Thesis Outline .................................................................................................................... 15 Chapter 2 .......................................................................................................................16 ix Literature Review ......................................................................................................16 2.1 Traditional methods to solve DMOPs ............................................................................. 16 2.1.1 The weighted sum ......................................................................................................
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