Using simulated annealing to design good codes
IEEE Transactions on Information Theory
An updated table of minimum-distance bounds for binary linear codes
IEEE Transactions on Information Theory
Parallel Genetic Simulated Annealing: A Massively Parallel SIMD Algorithm
IEEE Transactions on Parallel and Distributed Systems
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Solving the error correcting code problem with parallel hybrid heuristics
Proceedings of the 2004 ACM symposium on Applied computing
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
The Art of Error Correcting Coding
The Art of Error Correcting Coding
A table of upper bounds for binary codes
IEEE Transactions on Information Theory
Benchmarking a wide spectrum of metaheuristic techniques for the radio network design problem
IEEE Transactions on Evolutionary Computation
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Error Correcting Codes (ECCs) play an important role, for example, in the transmission of messages over telecommunication networks or in reading information from digital data media such as DVDs or CDs. The design of ECCs is computationally a hard problem. Due to its hardness, several metaheuristic approaches for its solution have been proposed in the literature. In this paper, we present different algorithms based on solution construction and iterated local search. The experimental evaluation shows that a simple multistart constructive heuristic is often between two and three orders of magnitude faster than current state-of-the-art metaheuristics when applied to rather small problem instances. When bigger problem instances are concerned, the proposed iterated local search algorithm has advantages over both the multistart constructive heuristic and state-of-the-art metaheuristics.