Evolutionary algorithms and matroid optimization problems

We analyze the performance of evolutionary algorithms on various matroid optimization problems that encompass a vast number of efficiently solvable as well as NP-hard combinatorial optimization problems (including many well-known examples such as minimum spanning tree and maximum bipartite matching). We obtain very promising bounds on the expected running time and quality of the computed solution. Our results establish a better theoretical understanding of why randomized search heuristics yield empirically good results for many real-world optimization problems. Categories and Subject Descriptors G.2.1 [Combinatorics]: Combinatorial algorithms; F.2.2 [Nonnumerical Algorithms and Problems]: Computations on discrete structures General Terms Theory, Algorithms, Performance Keywords evolutionary algorithms, matroids, minimum weight basis, matroid intersection, randomized search heuristics

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Joachim Reichel, Martin Skutella
• Keywords: Evolutionary Algorithms, GECCO 2007, Matroid Optimization Problems, Optimization Problems