SAGA: Demonstrating the Benefits of Commonality-Based Crossover Operators in Simulated Annealing

摘要: The crossover operator is traditionally viewed as the distinguishing feature and primary strength of a genetic algorithm. This multi-parent can recombine useful features two parent solutions into single “super” offspring. However, new analysis suggests that benefit operators preservatio n common components. In creating an offspring solution, focus its changes on uncommon components parents. surprisingly important algorithms. To demonstrate contribution preserving to search process algorithms, this has been isolated transferred simulated annealing. Results Travelling Salesman Problem indicate preservation lead significant improvements in performance