INTRODUCTION
Most combinatorial optimization problems, involving optimization of the topologies and configurations of very large-scale systems such as computer communication systems, reliability systems, manufacturing, robotics and traffic systems, are NP-hard problems. Well-known methods for large-scale combinatorial optimization are simulated annealing (Kirkpatrick, Gelatt and Vecchi, 1983; Romejn and Smith, 1994), tabu search (Glover, 1996), and genetic algorithms (Goldberg, 1989). Recent work on combinatorial optimization includes the nested partitioning method of Shi and Olafsson (1998), the stochastic comparison method of Gong, Ho and Zhai (1996), the method of Andradóttir, 1996, the method of Norkin, Pflug and Ruszczyński, (where the classical deterministic branch-and-bound is extended to stochastic problems) and the simulated entropy (SE) method, which is presented below (Rubinstein, 1999).
To find the optimal solution of a combinatorial problem, SE solves a sequence of simple...
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Rubinstein, R.Y. (2001). Combinatorial optimization by simulated cross-entropy . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_131
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DOI: https://doi.org/10.1007/1-4020-0611-X_131
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