Sequential and Parallel Branch-and-Bound Search Under Limited-Memory Constraints (1999)
| Venue: | in: P. Pardalos (Ed.), The IMA Volumes in Mathematics and its Applications—Parallel Processing of Discrete Problems |
| Citations: | 2 - 1 self |
BibTeX
@INPROCEEDINGS{Mahapatra99sequentialand,
author = {Nihar R. Mahapatra and Shantanu Dutt},
title = {Sequential and Parallel Branch-and-Bound Search Under Limited-Memory Constraints},
booktitle = {in: P. Pardalos (Ed.), The IMA Volumes in Mathematics and its Applications—Parallel Processing of Discrete Problems},
year = {1999},
pages = {139--158},
publisher = {Springer}
}
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Abstract
Branch-and-bound (B&B) best-first search (BFS) is a widely applicable method that requires the least number of node expansions to obtain optimal solutions to combinatorial optimization problems (COPs). However, for many problems of interest, its memory requirements are enormous and can far exceed the available memory capacity on most systems. To circumvent this problem, a number of limited-memory search methods have been proposed that are either based purely on depth-first search (DFS) or combine BFS with DFS. We survey and compare previous sequential and parallel limited-memory search methods, and discuss their suitability for solving different types of COPs. We also propose a new limited-memory search method, iterative extrapolated-cost bounded search (IECBS), that performs a sequence of cost-bounded depth-first searches from the root node of the search space. In this method, cost bounds for successive iterations are set to an estimated optimal-solution cost obtained by ext...
