Communication Strategies in Distributed Evolutionary Algorithms for Multi-objective Optimization
نویسندگان
چکیده
The communication between subpopulations in a distributed evolutionary algorithm is an important issue since it influences the algorithm effectiveness in solving the optimization problem and the efficiency of the parallel implementation. Choosing the adequate communication strategy depends on various factors, thus by comparing different strategies one can collect knowledge on how to design an effective approach. The aim of this paper is to compare a set of communication strategies both with respect to their effectiveness in approximating the Pareto set of a multi-objective optimization problem and with respect to the efficiency of a parallel implementation.
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