att_abstract={{ We investigate a variant of the many-to-many hub location-routing problem which consists in partitioning the set of nodes of a graph into routes containing exactly one hub each, and determining an extra route interconnecting all hubs. A variable neighborhood descent with neighborhood structures based on remove/add, swap and exchange moves nested with routing and location operations is used as a local search procedure in a multi-start algorithm.  We also consider a sequential version of this local search in the multi-start. In addition, a biased random-key genetic algorithm working with a local search routine, which also considers routing and location operations, is applied to the problem.  To compare the heuristic solutions, we develop an integer programming formulation which is solved with a branch-and-cut algorithm.  Capacity and path elimination constraints are added in a cutting plane fashion.  The separation algorithms are based on the computation of min-cut trees and on the connected components of a support graph.  Computational experiments were conducted on several benchmark instances of routing problems and show that the heuristics are effective on medium to large-sized instances, while the branch-and-cut algorithm solves small to medium sized problems to optimality.  These algorithms were also compared with a commercial hybrid solver showing that the heuristics are quite competitive.}},
	att_categories={C_CCF.8, C_CCF.7, C_NSS.8},
	att_copyright_notice={{The definitive version was published in Networks, John Wiley & Sons publications. {{, Volume 68}}{{, Issue 1}}{{, 2016-07-29}}
	att_tags={Hub location-routing problem,  heuristics,  variable neighborhood descent,  biased random-key genetic algorithm,  integer formulation},
	author={Mauro Cardoso Lopes and Carlos eduardo De andrade and Thiago Alves de Queiroz and Mauricio G. C. Resende and Flavio Keidi Miyazawa},
	institution={{Networks, John Wiley & Sons publications}},
	title={{Heuristics for a hub location-routing problem}},