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Abstract(s)
In real-world applications, the runtime of genetic algorithms (GAs) can be computationally demanding, an issue that can be mitigated using parallelization. The study evaluates the parallelization of order-based GAs using the island model in an asynchronous heterogeneous computing environment. The island model allows for a considerable number of migration topologies. The study offers a systematic review of the studies on migration topologies and observes that no study is available yet on the performance of these migration topologies over asynchronous heterogeneous environments. Based on a statistical analysis of a comprehensive set of experiments, using real-world TSPLIB instances, the study researches the question: What is the fastest island model topology for order-based genetic algorithm, in an asynchronous distributed heterogeneous grid-enabled commodity computing environment, without losing significant fitness comparatively to the correspondent sequential panmictic implementation of the same algorithm?. Moreover, a new speedup index, the expected root speedup, is also proposed. A diversity of topology types and characteristics are considered: the single node, star, ring, cartwheel, rooted ordered tree, rooted full binary tree, coordinated tree-ring, and feedforward fully connected layered type. Different number of nodes are also considered. While some of the types of topologies are well known, the coordinated tree-ring topology is a novelty. These types of topologies allow us to assess three notable cases: (i) no migration (isolated island), (ii) migration toward the coordinator only, and (iii) migration flows to, and from, the coordinator.
Description
Keywords
Traveling Salesman Problem Genetic Algorithms Island Model Evolutionary Cluster Implementation
Citation
Publisher
Springer