Deterministic Tournament Selection in Local Search for Maximum Edge Weight Clique on Large Sparse Graphs

• Published in: AI 2017: Advances in Artificial Intelligence pp. 353 - 364
• Main Authors: Ma, Zongjie, Fan, Yi, Su, Kaile, Li, Chengqian, Sattar, Abdul
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Large sparse graphs; Local search; Maximum edge weight clique
• ISBN: 9783319630038; 3319630032
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-63004-5_28

The maximum edge weight clique (MEWC) problem is important in both theories and applications. During last decades, there has been much interest in finding optimal or near-optimal solutions to this problem. Many existing heuristics focuses on academic benchmarks of relatively small size. However, very little attention has been paid to solving the MEWC problem in large sparse graphs. In this work, we exploit the so-called deterministic tournament selection (DTS) strategy to improve the local search MEWC algorithms. Experiments conducted on a broad range of large sparse graphs show that our algorithm outperforms state-of-the-art local search algorithms in this benchmark. Moreover it finds better solutions on a list of them.