An efficient algorithm for the minimum capacity cut problem
Mathematical Programming: Series A and B
The precedence-constrained asymmetric traveling salesman polytope
Mathematical Programming: Series A and B
Integer Programming Formulation of Traveling Salesman Problems
Journal of the ACM (JACM)
Invited review: A comparative analysis of several asymmetric traveling salesman problem formulations
Computers and Operations Research
The pickup and delivery traveling salesman problem with first-in-first-out loading
Computers and Operations Research
A comparison of five heuristics for the multiple depot vehicle scheduling problem
Journal of Scheduling
The double traveling salesman problem with multiple stacks: A variable neighborhood search approach
Computers and Operations Research
A branch-and-cut algorithm for the pickup and delivery traveling salesman problem with LIFO loading
Networks - Networks Optimization Workshop, August 22–25, 2006
The Traveling Salesman Problem with Pickups, Deliveries, and Handling Costs
Transportation Science
A large neighbourhood search heuristic for ship routing and scheduling with split loads
Computers and Operations Research
A maritime inventory routing problem: Practical approach
Computers and Operations Research
Hi-index | 0.02 |
In maritime transportation, routing decisions are sometimes affected by draft limits in ports. The draft of a ship is the distance between the waterline and the bottom of the ship and is a function of the load onboard. Draft limits in ports can thus prevent ships to enter these ports fully loaded and may impose a constraint on the sequence of visits made by a ship. This paper introduces the Traveling Salesman Problem with Draft Limits (TSPDL), which is to determine an optimal sequence of port visits under draft limit constraints. We present two mathematical formulations for the TSPDL, and suggest valid inequalities and strengthened bounds. We also introduce a set of instances based on TSPLIB. A branch-and-cut algorithm is applied on both formulations for all these instances. Computational results show that introducing draft limits make the problem much harder to solve. They also indicate that the proposed valid inequalities and strengthened bounds significantly reduce both the number of branch-and-bound nodes and the solution times.