Minimum spanning trees made easier via multi-objective optimization

Natural Computing

Volumn 5, Issue 3, 2006, Pages 305-319

  Neumann, Frank ^a   Wegener, Ingo ^b  

^a UNIVERSITY OF KIEL   (Germany)

^b TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Multi objective optimization; Running time analysis; Working principles of evolutionary computing

Indexed keywords

ALGORITHM; ARTICLE; CONTROLLED STUDY; EXPERIMENT; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; PROBLEM SOLVING;

EID: 33748121602     PISSN: 15677818     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11047-006-9004-x     Document Type: Article

References (16)

1. Briest P, Brockhoff D, Degener B, Englert M, Gunia C, Heering O, Jansen T, Leifhelm M, Plociennik K, Röglin H, Schweer A, Sudholt D, Tannenbaum S and Wegener I (2004) Experimental supplements to the theoretical analysis of EAs on problems from combinatorial optimization. In Proc. of the 8th Int. Conf. on Parallel Problem Solving from Nature (PPSN VIII). LNCS 3242: 21-30
2. Coello Coello CA, Van Veldhuizen DA, and Lamont GB (2002) Evolutionary algorithms for solving multi-objective problems. Kluwer Academic Publishers, New York
3. Cormen T, Leiserson C, Rivest R, and Stein C (2001) Introduction to Algorithms. 2nd edn., McGraw Hill, New York
4. Deb K (2001) Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester
5. Droste S, Jansen T, and Wegener I (2002) On the analysis of the (1+1) evolutionary algorithm. Theoretical Computer Science 276: 51-81
6. Ehrgott M (2000) Approximation algorithms for combinatorial multicriteria optimization problems. Interantional Transactions in Operational Research 7: 5-31
7. Giel O (2003) Expected runtimes of a simple multi-objective evolutionary algorithm. In Proc. of the 2003 Congress of Evolutionary Computation (CEC), 1918-1925
8. Giel O and Wegener I (2003) Evolutionary algorithms and the maximum matching problem. In Proc. of the 20th Ann. Symp. on Theoretical Aspects of Computer Science (STACS). LNCS 2607: 415-426
9. Hamacher HW and Ruhe G (1994) On spanning tree problems with multiple objectives. Annals of Operations Research 52: 209-230
10. Laumanns M, Thiele L, Zitzler F, Welzl E and Deb K (2002) Running time analysis of multi-objective evolutionary algorithms on a simple discrete optimization problem. Proc. of the 7th Int. Conf. on Parallel Problems Solving from Nature (PPSN VII). LNCS 2439: 44-53
11. Neumann F (2004) Expected run times of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem. In Proc. of the 8th. Int. Conf. on Parallel Problem Solving from Nature (PPSN VIII). LNCS 3242: 80-89
12. Neumann F and Wegener I (2004) Randomized local search, evolutionary algorithms, and the minimum spanning tree problem. In Proc. of Genetic and Evolutionary Computation Conference (GECCO 2004). LNCS 3102: 713-724
13. Raidl GR and Julstrom BA (2003) Edge sets: An effective evolutionary coding of spanning trees. IEEE Transactions on Evolutionary Computation 7: 225-239
14. Scharnow J, Tinnefeld K and Wegener I (2002). Fitness landscapes based on sorting and shortest paths problems. Proc. of the 7th Conf. on Parallel Problem Solving from Nature (PPSN VII). LNCS 2439: 54-63
15. Zhou G and Gen M (1999) Genetic algorithm approach on multi-criteria minimum spanning tree problem. European Journal of Operational Research 114: 141-152
16. Zitzler E, Laumanns M, Thiele L, Fonseca CM and Grunert da Fonseca V (2003) Performance assessment of multi-objective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation 7: 117-132