GAVEL - a new tool for genetic algorithm visualization

• Published in: IEEE transactions on evolutionary computation Vol. 5; no. 4; pp. 335 - 348
• Main Authors: Hart, E., Ross, P.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2001; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Artificial intelligence; Assembly; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Councils; Evolutionary algorithms; Evolutionary computation; Exact sciences and technology; Genetic algorithms; Genetic mutations; History; Mutations; Operators; Pattern recognition. Digital image processing. Computational geometry; Scheduling; Software; State of the art; Thumb; Turning; Visualization; Production system; Visualization; Scheduling; Genetic algorithm; Evolutionary algorithm
• ISSN: 1089-778X; 1941-0026
• DOI: 10.1109/4235.942528

This paper surveys the state of the art in evolutionary algorithm visualization and describes a new tool called GAVEL. It provides a means to examine in a genetic algorithm (GA) how crossover and mutation operations assembled the final result, where each of the alleles came from, and a way to trace the history of user-selected sets of alleles. A visualization tool of this kind can be very useful in choosing operators and parameters and in analyzing how and, indeed, whether or not a GA works. We describe the new tool and illustrate some of the benefits that can be gained from using it with reference to three different problems: a timetabling problem, a job-shop scheduling problem, and Goldberg and Horn's long-path problem. We also compare the tool to other available visualization tools, pointing out those features which are novel and identifying complementary features in other tools.