Treffer: Decomposing non-product form queuing lattices through genetic algorithm

In this paper, a Genetic Algorithm technique is adapted to decompose the state transition lattice of a class of non-product form queueing models. Genetic Algorithms are search algorithms based upon the mechanics of natural genetics. They combine a survival-of-the-fittest among string structures with a structured, yet randomized, information exchange to form a search algorithm with some of the innovative flair of human search. While randomized, genetic algorithms are no simple random walk. They efficiently exploit historical information to speculate on new search points with improved performance. Here genetic algorithms is applied to a non-product queueing lattices optimization problem. Only the lattice of type A structure are considered. By applying this technique, the lattice is decomposed into solvable subsets which can be solved sequentially and independently.