Distributed Collective Adaptation Applied to a Hard Combinatorial Optimization Problem

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@InProceedings{Haynes:1999:DCAa,

• author = "Thomas Haynes",
• title = "Distributed Collective Adaptation Applied to a Hard Combinatorial Optimization Problem",
• booktitle = "Proceedings of the 1999 ACM Symposium on Applied Computing",
• year = "1999",
• editor = "Janice Carroll and Hisham Haddad and Dave Oppenheim and Barrett Bryant and Gary B. Lamont",
• pages = "339--343",
• publisher = "ACM Press",
• keywords = "genetic algorithms, genetic programming",
• broken = "http://adept.cs.twsu.edu/~thomas/mpi.ps",
• URL = "http://delivery.acm.org/10.1145/300000/298377/p339-haynes.pdf",
• DOI = "doi:10.1145/298151.298377",
• size = "5 pages",
• abstract = "We use collective memory to integrate weak and strong search heuristics to find cliques in FC, a family of graphs. We construct FC such that pruning partial solutions will be ineffective. Each weak heuristic maintains a local cache of the collective memory. We examine the impact on the distributed search of the distribution of the collective memory, the search algorithms, and our family of graphs. We find the distributed search performs better than the individual searches, even though the space of partial solutions is combinatorial.",
• notes = "(GA track)",

}

Genetic Programming entries for Thomas D Haynes

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