Reduced Cost-Based Ranking for Generating Promising Subproblems
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Discrepancy-Based Additive Bounding Procedures
INFORMS Journal on Computing
A Compressed-Annealing Heuristic for the Traveling Salesman Problem with Time Windows
INFORMS Journal on Computing
Proactive algorithms for job shop scheduling with probabilistic durations
Journal of Artificial Intelligence Research
Beam-ACO for the travelling salesman problem with time windows
Computers and Operations Research
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Discrepancy-based sliced neighborhood search
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
Improving CP-based local branching via sliced neighborhood search
Proceedings of the 2011 ACM Symposium on Applied Computing
Optimization of the nested Monte-Carlo algorithm on the traveling salesman problem with time windows
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Checking the Feasibility of Dial-a-Ride Instances Using Constraint Programming
Transportation Science
Expert Systems with Applications: An International Journal
A General VNS heuristic for the traveling salesman problem with time windows
Discrete Optimization
The Delivery Man Problem with time windows
Discrete Optimization
Bounding, filtering and diversification in CP-based local branching
Journal of Heuristics
A Hybrid Tabu Search and Constraint Programming Algorithm for the Dynamic Dial-a-Ride Problem
INFORMS Journal on Computing
New State-Space Relaxations for Solving the Traveling Salesman Problem with Time Windows
INFORMS Journal on Computing
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Optimal valve placement in water distribution networks with CLP(FD)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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TheTraveling Salesman Problem with Time Windows (TSPTW) is the problem of finding a minimum-cost path visiting a set of cities exactly once, where each city must be visited within a specific time window. We propose a hybrid approach for solving the TSPTW that merges Constraint Programming propagation algorithms for the feasibility viewpoint (find a path), and Operations Research techniques for coping with the optimization perspective (find the best path). We show with extensive computational results that the synergy between Operations Research optimization techniques embedded in global constraints, and Constraint Programming constraint solving techniques, makes the resulting framework effective in the TSPTW context also if these results are compared with state-of-the-art algorithms from the literature.