Nested Partitions Method for Global Optimization

By Leyuan Shi, Sigurdur Olafsson. Operational Research, 2000

378 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Numerical Analysis, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a9d055363e1fc0a88a753f1f5d6554f05e7d93a3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Andrea Roli
2. Jakob Puchinger
3. Günther R. Raidl
4. Christian Blum
5. Michael C. Fu
6. Vladimir A. Grishagin
7. Alexander Gergel
8. Victor P. Gergel

In Numerical Analysis

1. Vladimir A. Grishagin
2. Günther R. Raidl
3. Christian Blum
4. Michael C. Fu
5. Andrea Roli
6. Alexander Gergel
7. Jakob Puchinger
8. Victor P. Gergel

In Signal Processing

1. Günther R. Raidl
2. Christian Blum
3. Michael C. Fu
4. Andrea Roli
5. Vladimir A. Grishagin
6. Alexander Gergel
7. Jakob Puchinger
8. Victor P. Gergel

Citations in the corpus

• Adaptive nested optimization scheme for multidimensional global search (2015, methodology): “According to this scheme, the solving of a multidimensional optimization problem could be obtained by means of solving a sequence of the recursively nested one-dimensional problems (see, for example [2,3,8,12,25,28,31,36]).”
• Hybrid metaheuristics in combinatorial optimization: A survey (2011, methodology): “Nested partitioning proposed by Shi and ´Olafsson [121] is another example were breadth-first search combined with backtracking is used to explore the search space under the guidance of a metaheuristic.”
• Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning (2016, neutral): “For instance, in [43], a randomized branching heuristic algorithm called nested partitioning is presented, which shares many similarities with an early-terminating B&B algorithm.”
• A Tutorial on the Cross-Entropy Method (2005, neutral): “Recent related work on randomized combinatorial optimization includes the nested partitioning method ( Shi and Olafsson, 2000 ) and the ant colony optimization meta-heuristic (Colorni et al., 1996; Dorigo, Di Caro, and Gambardella, 1999; Gutjahr, 2000).”
• Optimization for Simulation: Theory vs. Practice (2002, background): “Space and scope limitations preclude discussion of some newly developed techniques in combinatorial optimization that may hold potential for application to the stochastic simulation setting, but two fairly recent approaches that have showed promise include ant colony optimization (see Dorigo and Di ”