Lexicographic codes: Error-correcting codes from game theory
IEEE Transactions on Information Theory
Using simulated annealing to design good codes
IEEE Transactions on Information Theory
Handbook of combinatorics (vol. 1)
A geometric approach to finding new lower bounds of A(n, d, w)
Designs, Codes and Cryptography
Upper bounds for constant-weight codes
IEEE Transactions on Information Theory
Index to constant weight codeword converter
ARC'11 Proceedings of the 7th international conference on Reconfigurable computing: architectures, tools and applications
A new table of permutation codes
Designs, Codes and Cryptography
| Hi-index | 754.84 |
Constant weight binary codes are used in a number of applications. Constructions based on mathematical structure are known for many codes. However, heuristic constructions unrelated to any mathematical structure can become of greater importance when the parameters of the code are larger. This paper considers the problem of finding constant weight codes with the maximum number of codewords from a purely algorithmic perspective. A set of heuristic and metaheuristic methods is presented and developed into a variable neighborhood search framework. The proposed method is applied to 383 previously studied cases with lengths between 29 and 63. For these cases it generates 153 new codes, with significantly increased numbers of codewords in comparison with existing constructions. For 10 of these new codes the number of codewords meets a known upper bound, and so these 10 codes are optimal. As well as the ability to generate new best codes, the approach has the advantage that it is a single method capable of addressing many sets of parameters in a uniform way.