New PDF release: 4th Int'l Conference on Numerical Methods in Fluid Dynamics
By R.D. Richtmyer
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Extra info for 4th Int'l Conference on Numerical Methods in Fluid Dynamics
C. -P. Watson landscape. We refer to this force as drift. The influence of drift on the outcome of local search depends on how well the connectivity of the landscape matches the overlying objective function. In case of a regular graph no drift exists. We conjecture this to be an important prerequisite for measuring the autocorrelation of a landscape as described above. This is commonly expressed by the assumption of a statistically isotropic landscape. However, as shown in the next section, the configuration space of combinatorial optimization problems are not always regular.
Garey and Johnson (1979) show that this problem belongs to the class of NP-hard problems. Hence, exact solution techniques are bound to work well for small to medium sized problem instances only and real world sized problems including up to thousands of items have to be solved heuristically. In recent years, meta-heuristic approaches have been applied to the onedimensional BPP at the forefront of which algorithms based on evolutionary concepts have to be mentioned. Falkenauer (1996) developed a Hybrid Grouping Genetic Algorithm (HGGA) which to date is the most effective mate-heuristic approach for the one-dimensional BPP.
Operations Research, 40:113–125, 1992. 15. C. Mattfeld. Evolutionary Search and the Job Shop. Physica-Verlag, 1996. 16. C. Mattfeld, C. Bierwirth, and H. Kopfer. A search space analysis of the job shop scheduling. Annals of Operations Research, 86:441–453, 1999. 17. P. Merz and B. Freisleben. Fitness landscape analysis and memetic algorithms for the quadratic assignment problem. IEEE Transactions on Evolutionary Computation, 4:337–352, 2000. 18. E. Nowicki and S. Smutnicki. A fast tabu search algorithm for the job shop problem.
4th Int'l Conference on Numerical Methods in Fluid Dynamics by R.D. Richtmyer