1. Garey, M.R., Johnson, D.S.: Computers and intractability-A guide to the theory of NP-completeness. Freeman, New York (1979)

   MATH  Google Scholar 

2. Hochbaum, D.S.: Approximation algorithms for NP-Hard problems. Wadworth publish company (1997)

   Google Scholar 

3. Michalewicz, Z.: Genetic algorithms + data structures = Evolution programs. Springer, Heidelberg (1992)

   MATH  Google Scholar 

4. Wang, R.: A genetic algorithm for subset sum problem. Neurocomputing, 463–468 (2004)

   Google Scholar 

5. Lin, F.T., Kao, C.Y., Hsu, C.C.: Applying the genetic approach to simulated annealing in solving some NP-hard problems. IEEE transactions on system, man, and cybernetics 23, 1752–1767 (1993)

   Article  Google Scholar 

6. Witt, C.: Worst-case and average-case approximations by simple randomized search heuristics. In: Diekert, V., Durand, B. (eds.) STACS 2005. LNCS, vol. 3404, pp. 44–56. Springer, Heidelberg (2005)

   Google Scholar 

7. Beyer, H.-G., Schwefel, H.-P., Wegener, I.: How to analyze evolutionary algorithms. Theoretical Computer Science, 101–130 (2002)

   Google Scholar 

8. Garnier, J., Kallel, L., Schoenauer, M.: Rigorous hitting times for binary mutations. Evolutionary Computation, 167–203 (1999)

   Google Scholar 

9. Droste, S., Jansen, T., Wegener, I.: On the analysis of the (1+1)-evolutionary algorithm. Theoretical Computer Science, 51–81 (2002)

   Google Scholar 

10. Wegener, I., Witt, C.: On the analysis of a simple evolutionary algorithm on quadratic pseudo-boolean function. Journal of discrete algorithms, 61–78 (2005)

    Google Scholar 

11. He, J., Yao, X.: Towards an analytic framework for analyzing the computation time of evolutionary algorithms. Artificial Intelligence, 59–97 (2003)

    Google Scholar 

12. Iosifescu, M.: Finite Markov processes and their applications. John Wiley & Sons, Chichester (1980)

    MATH  Google Scholar 

13. Coello, C.A.C.: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Computer methods in applied mechanics and engineering 19, 1245–1287 (2002)

    Article  Google Scholar 

14. Deb, K.: An efficient constraint handling method for genetic algorithms. Computer methods in applied mechanics and engineering 186(2-4), 311–338 (2000)

    Article MATH  Google Scholar 

15. Coffman, J.W.W.: Recent asymptotic results in the probabilistic analysis of schedule makespans. In: Scheduling Theory and its applications, pp. 15–31. Wiley, Chichester (1995)

    Google Scholar 

16. Motwani, R., Raghavan, P.: Randomized algorithms. Cambridge University Press, Cambridge (1995)

    MATH  Google Scholar 

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