@inproceedings{5932bfb1bb6f4fc0abd45ba3421c248e,

title = "Scalability and efficiency of genetic algorithms for geometrical applications",

abstract = "We study the scalability and efficiency of a GA that we developed earlier to solve the practical cartographic problem of labeling a map with point features. We argue that the special characteristics of our GA make that it fits in well with theoretical models predicting the optimal population size (the Gambler{\textquoteright}s Ruin model) and the number of generations until convergence. We then verify these predictions experimentally. It turns out that our algorithm indeed performs according to the theory, leading to a scale-up for the total amount of computational effort that is linear in the problem size.",

author = "{Dijk, van}, S.F. and D. Thierens and {Berg, de}, M.",

year = "2000",

doi = "10.1007/3-540-45356-3_67",

language = "English",

isbn = "3-540-41056-2",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "683--692",

editor = "M. Schoenauer",

booktitle = "Parallel Problem Solving from Nature (Proceedings 6th International Conference, PPSN-VI, Paris, France, September 18-20, 2000)",

address = "Germany",

}