Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Garrison Greenwood
Dr. Hossein Mousavineshad
Dr. Damon Miller
Masters Thesis-Open Access
The exponentially large size of the solution space of typical optimization problems precludes the use of any deterministic approach to search for an optimal solution. A more efficient and efficacious approach is to use heuristic algorithms based on rules of thumb to guide the search process in the solution space. Associated with every solution in the space is a real number called fitness that signifies the quality of a solution. This space and the fitness values together form the fitness landscapes. Knowledge about the topology of these fitness landscapes is vital for any heuristic search operator to expedite the search process and also, find a good solution.
Complete enumeration of the landscape is usually impractical. Moreover, the landscape is often n-dimensional with n >> 3, making it difficult to visualize. This research deals with the development of mathematical and graphical techniques to characterize the structure of fitness landscapes. A new 3-D graphical tool that can depict the topology of high dimensional fitness landscapes has been developed. This graphical approach provides a visual perception of the space to be explored, which can be used to guide and accelerate the search process.
Ravichandran, Sai Prasanna, "Fitness Landscape Analysis of Discrete Constrained Optimization Problems" (1998). Master's Theses. 4238.