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Reduction approaches for robust shortest path problems
被引:23
作者:
Catanzaro, Daniele
[1
]
Labbe, Martine
[1
]
Salazar-Neumann, Martha
[1
]
机构:
[1] Univ Libre Bruxelles, Dept Comp Sci, B-1050 Brussels, Belgium
关键词:
Minimax regret optimization;
Robust optimization;
Shortest path problem;
Interval data;
Preprocessing;
Pegging test;
INTERVAL DATA;
ALGORITHM;
D O I:
10.1016/j.cor.2011.01.022
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
We investigate the uncertain versions of two classical combinatorial optimization problems, namely the Single-Pair Shortest Path Problem (SP-SPP) and the Single-Source Shortest Path Problem (SS-SPP). The former consists of finding a path of minimum length connecting two specific nodes in a finite directed graph G; the latter consists of finding the shortest paths from a fixed node to the remaining nodes of G. When considering the uncertain versions of both problems we assume that cycles may occur in G and that arc lengths are (possibly degenerating) nonnegative intervals. We provide sufficient conditions for a node and an arc to be always or never in an optimal solution of the Minimax regret Single-Pair Shortest Path Problem (MSP-SPP). Similarly, we provide sufficient conditions for an arc to be always or never in an optimal solution of the Minimax regret Single-Source Shortest Path Problem (MSS-SPP). We exploit such results to develop pegging tests useful to reduce the overall running time necessary to exactly solve both problems. (C) 2011 Elsevier Ltd. All rights reserved.
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页码:1610 / 1619
页数:10
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