A new iterated local search algorithm using genetic crossover for the traveling salesman problem

This paper proposes a new iterared local search (ILS) algorit.hm ihar escapes from local optima usin, a geuet ic crossover. In usual IL9 for solving the rraveling salesman problem, a double-bridge 4change move is geuerally employed as a useful technique to escape from t.he local opt ima fouud by a local search procedure. Proposed ILS uses a technique of crossover developed in a field of the genetic algorit.hms in spite of the double-bridge move. In our algorithm, !ve emplo\the disrauce preserviug crossover (UPX) proposed by Freislebeu and Merz. Therefore rhis DPS is performed as a special k-change ulove according to srates of t.wo solutions Lbat ueed fol crossover process. Experimeutal results demoust.rate t.hat proposed ILS Buds much better quality solutions than usual ILS using the double-bridge move. (:ousequeut.ly. this paper will show au efrect to employ tbe genet.ic crossover as the escape t.echuique.