FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
A parallel and distributed meta-heuristic framework based on partially ordered knowledge sharing
Journal of Parallel and Distributed Computing
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Although evolutionary algorithm is a powerful optimization tool, its computation cost involved in terms of time and hardware resources increases as the size or complexity of the problem increases. One promising approach to overcome this limitation is to exploit the inherent parallelism of evolutionary algorithms by creating an infrastructure necessary to support distributed evolutionary computing using existing Internet and hardware resources. This paper presents a Java-based distributed evolutionary computing software (Paladin-DEC), which enhances the concurrent processing and performance of evolutionary algorithms by allowing inter-communications of subpopulations among various computers over the Internet. Such a distributed system enables individuals to migrate among multiple subpopulations according to some patterns to induce diversity of elite individuals periodically, in a way that simulates the species evolve in natural environment. The Paladin-DEC software is capable of keeping data integrity throughout the computation, and is incorporated with the features of robustness, security, fault tolerance, and work balancing. The effectiveness and advantages of the Paladin-DEC are illustrated upon two case studies of drug scheduling in cancer chemotherapy and searching probe sets of yeast genome.