2015/08/07 by Kaarthik Sundar, Sundar, Kaarthik, Sivakumar Rathinam +1 · 1 citation
Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #G.2.1 #Maritime Ports and Logistics #Optimization and Packing Problems #Vehicle Routing Optimization Methods #cs.DS
paper · pdf · doi:10.48550/arxiv.1508.01813
26 pages
arxiv created 2015/08/07 · openalex publication_date 2015/08/07 · arxiv updated 2015/08/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The generalized multiple depot traveling salesmen problem (GMDTSP) is a variant of the multiple depot traveling salesmen problem (MDTSP), where each salesman starts at a distinct depot, the targets are partitioned into clusters and at least one target in each cluster is visited by some salesman. The GMDTSP is an NP-hard problem as it generalizes the MDTSP and has practical applications in design of ring networks, vehicle routing, flexible manufacturing scheduling and postal routing. We present an integer programming formulation for the GMDTSP and valid inequalities to strengthen the linear programming relaxation. Furthermore, we present a polyhedral analysis of the convex hull of feasible solutions to the GMDTSP and derive facet-defining inequalities that strengthen the linear programming relaxation of the GMDTSP. All these results are then used to develop a branch-and-cut algorithm to obtain optimal solutions to the problem. The performance of the algorithm is evaluated through extensive computational experiments on several benchmark instances.