Journal
RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING
Volume 11, Issue 3, Pages 260-266Publisher
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/2352096511666180214105643
Keywords
Genetic algorithms; network optimization; maximum clique; weight clique; genetic representation; genes
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Funding
- North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement [NORTE- 01-0145-FEDER-000020]
- European Regional Development Fund (ERDF) [POCI-01-0145- FEDER-006933-SYSTEC, PTDC/EEIAUT/2933/2014]
- FEDER/COMPETE2020-POCI/FCT
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Background: This work addresses the maximum edge weight clique problem (MEWC), an important generalization of the well-known maximum clique problem. Methods: The MEWC problem can be used to model applications in many fields including broadband network design, computer vision, pattern recognition, and robotics. We propose a random key genetic algorithm to find good quality solutions for this problem. Computational experiments are reported for a set of benchmark problem instances derived from the DIMACS maximum clique instances. Results: The results obtained show that our algorithm is both effective and efficient, as for most of the problem instances tested, we were able to match the best-known solutions with very small computational time requirements.
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