Column Generation Algorithms for the Capacitated m-Ring-Star Problem
COCOON '08 Proceedings of the 14th annual international conference on Computing and Combinatorics
On the Integration of a TSP Heuristic into an EA for the Bi-objective Ring Star Problem
HM '08 Proceedings of the 5th International Workshop on Hybrid Metaheuristics
Tight bounds from a path based formulation for the tree of hub location problem
Computers and Operations Research
Metaheuristics and cooperative approaches for the Bi-objective Ring Star Problem
Computers and Operations Research
Metaheuristics for the bi-objective ring star problem
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Improved formulations for the ring spur assignment problem
INOC'11 Proceedings of the 5th international conference on Network optimization
Designing Steiner Networks with Unicyclic Connected Components: An Easy Problem
SIAM Journal on Discrete Mathematics
An efficient heuristic for the ring star problem
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
A linear time algorithm for the minimum spanning caterpillar problem for bounded treewidth graphs
SIROCCO'10 Proceedings of the 17th international conference on Structural Information and Communication Complexity
An integer programming-based local search for the covering salesman problem
Computers and Operations Research
The non-disjoint m-ring-star problem: polyhedral results and SDH/SONET network design
ISCO'12 Proceedings of the Second international conference on Combinatorial Optimization
A column generation approach for a school bus routing problem with resource constraints
Computers and Operations Research
The traveling purchaser problem, with multiple stacks and deliveries: A branch-and-cut approach
Computers and Operations Research
A memetic algorithm for the capacitated m-ring-star problem
Applied Intelligence
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In the Ring Star Problem, the aim is to locate a simple cycle through a subset of vertices of a graph with the objective of minimizing the sum of two costs: a ring cost proportional to the length of the cycle and an assignment cost from the vertices not in the cycle to their closest vertex on the cycle. The problem has several applications in telecommunications network design and in rapid transit systems planning. It is an extension of the classical location–allocation problem introduced in the early 1960s, and closely related versions have been recently studied by several authors. This article formulates the problem as a mixed-integer linear program and strengthens it with the introduction of several families of valid inequalities. These inequalities are shown to be facet-defining and are used to develop a branch-and-cut algorithm. Computational results show that instances involving up to 300 vertices can be solved optimally using the proposed methodology. © 2004 Wiley Periodicals, Inc.