Parallel Genetic Algorithms for Hypercube Machines

In this paper we investigate the design of highly parallel Genetic Algorithms. The Traveling Salesman Problem is used as a case study to evaluate and compare different implementations. To fix the various parameters of Genetic Algorithms to the case study considered, the Holland sequential Genetic Algorithm, which adopts different population replacement methods and crossover operators, has been implemented and tested. Both fine-grained and coarse-grained parallel GAs which adopt the selected genetic operators have been designed and implemented on a 128-node nCUBE 2 multicomputer. The fine-grained algorithm uses an innovative mapping strategy that makes the number of solutions managed independent of the number of processing nodes used. Complete performance results showing the behaviour of Parallel Genetic Algorithms for different population sizes, number of processors used, migration strategies are reported.

[1]  Heinz Mühlenbein,et al.  The parallel genetic algorithm as function optimizer , 1991, Parallel Comput..

[2]  Erick Cantú-Paz,et al.  A Summary of Research on Parallel Genetic Algorithms , 1995 .

[3]  Heinrich Braun,et al.  On Solving Travelling Salesman Problems by Genetic Algorithms , 1990, PPSN.

[4]  Joachim Stender,et al.  Parallel Genetic Algorithms: Introduction and Overview of Current Research , 1993 .

[5]  Dana S. Richards,et al.  Distributed genetic algorithms for the floorplan design problem , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[6]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[7]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[8]  Martina Gorges-Schleuter,et al.  Genetic algorithms and population structures: a massively parallel algorithm , 1991 .

[9]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[10]  Christopher M. Brown,et al.  Parallel genetic algorithms on distributed-memory architectures , 1993 .

[11]  Reiko Tanese,et al.  Parallel Genetic Algorithms for a Hypercube , 1987, ICGA.

[12]  John J. Grefenstette,et al.  A Parallel Genetic Algorithm , 1987, ICGA.

[13]  David E. Goldberg,et al.  AllelesLociand the Traveling Salesman Problem , 1985, ICGA.

[14]  Heinz Mühlenbein,et al.  Parallel Genetic Algorithms in Optimization , 1991, Physik und Informatik.

[15]  Dana S. Richards,et al.  Punctuated Equilibria: A Parallel Genetic Algorithm , 1987, ICGA.

[16]  Martina Gorges-Schleuter,et al.  Explicit Parallelism of Genetic Algorithms through Population Structures , 1990, PPSN.

[17]  Bernard Manderick,et al.  Fine-Grained Parallel Genetic Algorithms , 1989, ICGA.

[18]  Paul Bryant Grosso,et al.  Computer Simulations of Genetic Adaptation: Parallel Subcomponent Interaction in a Multilocus Model , 1985 .

[19]  Reiko Tanese,et al.  Distributed Genetic Algorithms , 1989, ICGA.