GRASP for low autocorrelated binary sequences

Authors:
Huchen Wang;Shaowei Wang
Affiliations:
Nanjing University, School of Electronic Science and Engineering, China;Nanjing University, School of Electronic Science and Engineering, China
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

Citing 3
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Abstract

The search for low autocorrelated binary sequences(LABS) is a combinatorial optimization problem, which is NP-hard. In this paper, we apply Greedy Randomized Adaptive Search Procedures (GRASP) to tackle the LABS problem. The algorithm is capable of systematically recovering best-known solutions reported by now. Furthermore, it can find out good autocorrelated binary sequences sequences in considerably less time as comparison with other heuristic methods.