A biased random-key genetic algorithm for the Steiner triple covering problem

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Mauricio G C Resende (Author) Other; Rodrigo F Toso (Author) Other; Jose Fernando Goncalves (Author) FEP; Ricardo M A Silva (Author) Other

Journal

Title: Optimization Letters

Vol. 6 No. 4

Pages: 605-619

ISSN: 1862-4472

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 14 Citations

ISI Web of Science

Scopus - 16 Citations

Scientific classification

FOS: Engineering and technology > Industrial biotechnology

CORDIS: Social sciences > Economics > Management studies

Other information

Authenticus ID: P-002-B8V

DOI: 10.1007/s11590-011-0285-3

Abstract (EN): We present a biased random-key genetic algorithm (BRKGA) for finding small covers of computationally difficult set covering problems that arise in computing the 1-width of incidence matrices of Steiner triple systems. Using a parallel implementation of the BRKGA, we compute improved covers for the two largest instances in a standard set of test problems used to evaluate solution procedures for this problem. The new covers for instances A(405) and A(729) have sizes 335 and 617, respectively. On all other smaller instances our algorithm consistently produces covers of optimal size.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15