کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
242195 501811 2007 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Local search optimisation applied to the minimum distance problem
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Local search optimisation applied to the minimum distance problem
چکیده انگلیسی

In practical terms all coded electronic signals are prone to corruption during transmission but may be corrected by using error-correcting codes. The minimum distance of a code is important because it is the major parameter affecting the error-correcting performance of a code. In this paper a recent heuristic combinatorial optimisation algorithm, called ant colony optimisation (ACO), is applied to the problem of determining minimum distances of error-correcting codes.The ACO algorithm is motivated by analogy with natural phenomena, in particular, the ability of a colony of ants to ‘optimise’ their collective endeavours. In this paper the biological background for ACO is explained and its computational implementation is presented in an error-correcting code context. The particular implementation of ACO makes use of a tabu search (TS) improvement phase to give a computationally enhanced algorithm (ACOTS). Two classes of codes are then used to show that ACOTS is a useful and viable optimisation technique to investigate minimum distances of error-correcting codes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advanced Engineering Informatics - Volume 21, Issue 4, October 2007, Pages 391–397
نویسندگان
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