Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
A Framework for Distributed Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Takeover time curves in random and small-world structured populations
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Fault Tolerant Optimization Algorithm based on Evolutionary Computation
DEPCOS-RELCOMEX '06 Proceedings of the International Conference on Dependability of Computer Systems
Understanding churn in peer-to-peer networks
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
On the Intrinsic Fault-Tolerance Nature of Parallel Genetic Programming
PDP '07 Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
Is the island model fault tolerant?
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Exploring selection mechanisms for an agent-based distributed evolutionary algorithm
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Peer-to-peer evolutionary algorithms with adaptive autonomous selection
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue (1143 - 1198) " Distributed Bioinspired Algorithms"; Guest editors: F. Fernández de Vega, E. Cantú-Paz
A robust and scalable peer-to-peer gossiping protocol
AP2PC'03 Proceedings of the Second international conference on Agents and Peer-to-Peer Computing
Effects of scale-free and small-world topologies on binary coded self-adaptive CEA
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Improving genetic algorithms performance via deterministic population shrinkage
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
EvAg: a scalable peer-to-peer evolutionary algorithm
Genetic Programming and Evolvable Machines
Characterizing fault-tolerance of genetic algorithms in desktop grid systems
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
SofEA: a pool-based framework for evolutionary algorithms using CouchDB
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Designing and testing a pool-based evolutionary algorithm
Natural Computing: an international journal
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In this paper we analyse the resilience of a peer-to-peer (P2P) evolutionary algorithm (EA) subject to the following dynamics: computing nodes acting as peers leave the system independently from each other causing a collective effect known as churn. Since the P2P EA has been designed to tackle large instances of computationally expensive problems, we will assess its behaviour under these conditions, by performing a scalability analysis in five different scenarios using the massively multimodal deceptive problem as a benchmark. In all cases, the P2P EA reaches the success criterion without a penalty on the runtime. We show that the key to the algorithm resilience is to ensure enough peers at the beginning of the experiment; even if some of them leave, those that remain contain enough information to guarantee a reliable convergence.