GAVEL - a new tool for genetic algorithm visualization

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.

[1]  R. H. Stumpf,et al.  Graphical exploratory data analysis , 1986 .

[2]  Colin R. Reeves,et al.  Are Long Path Problems Hard for Genetic Algorithms? , 1996, PPSN.

[3]  Terry Jones,et al.  Crossover, Macromutationand, and Population-Based Search , 1995, ICGA.

[4]  Peter Ross,et al.  Fast Practical Evolutionary Timetabling , 1994, Evolutionary Computing, AISB Workshop.

[5]  Jacques Bertin,et al.  Graphics and graphic information-processing , 1981 .

[6]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[7]  William M. Spears,et al.  An Overview of Multidimensional Visualization Techniques , 1999 .

[8]  Tanja Dabs,et al.  A Graphical User Interface For Genetic Algorithms , 1995 .

[9]  Kenneth A. De Jong,et al.  An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms , 1990, PPSN.

[10]  Trevor Collins,et al.  Understanding evolutionary computing: a hands on approach , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[11]  Peter Ross,et al.  A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems , 1993, ICGA.

[12]  W. B. Shine,et al.  Visualizing the evolution of genetic algorithm search processes , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[13]  Hartmut Pohlheim,et al.  Visualization of evolutionary algorithms - set of standard techniques and multidimensional visualization , 1999 .

[14]  Trevor D. Collins.  Using Software Visualisation Technology to Help Evolutionary Algorithm Users Validate Their Solutions , 1997, ICGA.

[15]  Bart Naudts,et al.  Candidate Longpaths for the Simple Genetic Algorithm , 1998, FOGA.

[16]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[17]  S. Kirkpatrick,et al.  Configuration space analysis of travelling salesman problems , 1985 .

[18]  Kalyanmoy Deb,et al.  Long Path Problems , 1994, PPSN.

[19]  Xin Yao,et al.  On Evolving Robust Strategies for Iterated Prisoner's Dilemma , 1993, Evo Workshops.

[20]  Inman Harvey,et al.  Through the Labyrinth Evolution Finds a Way: A Silicon Ridge , 1996, ICES.

[21]  Hugh M. Cartwright,et al.  Looking Around: Using Clues from the Data Space to Guide Genetic Algorithm Searches , 1991, ICGA.

[22]  Trevor D. Collins,et al.  Visualization of Binary String Convergence by Sammon Mapping , 1996, Evolutionary Programming.

[23]  John W. Sammon,et al.  A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.

[24]  K.A. De Jong,et al.  Visual analysis of evolutionary algorithms , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[25]  Peter Ross,et al.  Adapting Operator Settings in Genetic Algorithms , 1998, Evolutionary Computation.

[26]  Mark A. Bedau,et al.  Visualizing Waves of Evolutionary Activity of Alleles , 1999 .

[27]  Murray H. Loew,et al.  The quadcode and its arithmetic , 1987, CACM.

[28]  Dirk C. Mattfeld,et al.  Evolutionary Search and the Job Shop - Investigations on Genetic Algorithms for Production Scheduling , 1996, Production and Logistics.