Parallel genetic algorithms for a hypercube
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Parallel programming with MPI
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy
Proceedings of the 3rd International Conference on Genetic Algorithms
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Fine-Grained Parallel Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
A Parallel Genetic Heuristic for the Quadratic Assignment Problem
Proceedings of the 3rd International Conference on Genetic Algorithms
Implementing the Genetic Algorithm on Transputer Based Parallel Processing Systems
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Implementation of Standard Genetic Algorithm on MIMD Machines
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
A Theoretical Investigation of a Parallel Genetic Algorithm
Proceedings of the 3rd International Conference on Genetic Algorithms
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In most of the popular implementation of Parallel GAs the whole population is divided into a set of subpopulations, each subpopulation executes GA independently and some individuals are migrated at fixed intervals on a ring topology. In these studies, the migrations usually occur 'synchronously' among subpopulations. Therefore, CPUs are not used efficiently and the communication do not occur efficiently either. A few studies tried asynchronous migration but it is hard to implement and to set proper parameter values. The aim of our research is to develop a migration method which is easy to implement, which is easy to set parameter values, and which reduces communication traffic. In our previous research, we proposed Elite Migration on the Server-Client topology and Layered Server-Client topology. In this paper, we consider the effectiveness of Layered Server-Client topology on Large Problem, especially on TSP with 2392 cities.