Date of Award
Spring 3-9-2012
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
First Advisor
Yan-Qing Zhang
Second Advisor
Raj Sunderraman
Third Advisor
YingShu Li
Fourth Advisor
Yichuan Zhao
Abstract
The Genetic Algorithm (GA) is a popular global search algorithm. Although it has been used successfully in many fields, there are still performance challenges that prevent GA’s further success. The performance challenges include: difficult to reach optimal solutions for complex problems and take a very long time to solve difficult problems. This dissertation is to research new ways to improve GA’s performance on solution quality and convergence speed. The main focus is to present the concept of shadow price and propose a two-measurement GA. The new algorithm uses the fitness value to measure solutions and shadow price to evaluate components. New shadow price Guided operators are used to achieve good measurable evolutions. Simulation results have shown that the new shadow price Guided genetic algorithm (SGA) is effective in terms of performance and efficient in terms of speed.
DOI
https://doi.org/10.57709/2721649
Recommended Citation
Shen, Gang, "Shadow Price Guided Genetic Algorithms." Dissertation, Georgia State University, 2012.
doi: https://doi.org/10.57709/2721649