On the flexibility of constraint programming models: from single to multiple time windows for the traveling salesman problem

Constraints can be removed or added to constraint programming models without any risk of destroying a certain problem structure on which the solution strategy depends. Such property enhances the resolution of variations in a traveling salesman problem by allowing easy adaptation of a constraint programming (CP) algorithm. Study shows that CP's growing impact in combinatorial optimization can be attributed to its flexible modeling capabilities.