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The state-of-the-art of local search heuristics for the traveling salesman problem (TSP) is chiefly based on algorithms using the classical Lin-Kernighan (LK) procedure and the stem-and-cycle (S&C) ejection chain method. Critical aspects of implementing these algorithms efficiently and effectively rely on taking advantage of special data structures and on maintaining appropriate candidate lists to store and update potentially available moves. We report the outcomes of an extensive series ofdoi:10.1016/j.cor.2005.06.014 fatcat:g5iof6dn7favppwwx7turhdlxu