Please use this identifier to cite or link to this item:
Type: Thesis
Title: Parameterized analysis of bio-inspired computation and the traveling salesperson problem.
Author: Nallaperuma, Samadhi Nethmini
Issue Date: 2015
School/Discipline: School of Computer Science
Abstract: Bio-inspired algorithms such as evolutionary algorithms (EA) and ant colony optimization (ACO) have become very popular in recent years to solve a wide range of complex real world problems. However, the understanding about the conditions under which these algorithms perform well is still limited. Classical computational complexity analysis often taking a worst case perspective, hardly captures what is happening during the actual algorithm run and, lacks implications for guiding algorithm design. This issue is more significant on the problems such as the traveling salesperson problem (TSP) where the problem is hard in a theoretical sense and has a lot of real world applications. Thus, more practical perspectives of algorithm analysis and design are essential to bridge the gap between the theory and the practice in bio-inspired computation specially with respect to the hard problems such as the TSP. We introduce “parameterized analysis” of bio-inspired computation by linking together several emerging methods of algorithm analysis and design with the aim of explaining the relationship between various problem and algorithm parameters and their effects on the algorithm performance. Moreover, we gain novel insights into bio-inspired computation and the TSP through parameterized analysis.
Advisor: Neumann, Frank
Michalewicz, Zbigniew
Dissertation Note: Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2015
Keywords: combinatorial optimization; traveling salesperson problem; evolutionary computation; ant colony optimization; parameterized complexity
Provenance: This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at:
Appears in Collections:Research Theses

Files in This Item:
File Description SizeFormat 
01front.pdf191.37 kBAdobe PDFView/Open
02whole.pdf7.88 MBAdobe PDFView/Open
PermissionsLibrary staff access only246.03 kBAdobe PDFView/Open
RestrictedLibrary staff access only7.82 MBAdobe PDFView/Open

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