We study a generalization of the Directed Rural Postman Problem where not all arcs requiring a service have to be visited provided that a penalty cost is paid if a service arc is not crossed. The problem, known as Directed Profitable Rural Postman Problem, looks for a tour visiting the selected set of service arcs while minimizing both traveling and penalty costs. We add different valid inequalities to a known mathematical formulation of the problem and develop a branch-and-cut algorithm that introduces connectivity constraints both in a “lazy” and in a standard way. We also propose a matheuristic followed by an improvement heuristic (final refinement). The matheuristic exploits information provided by a problem relaxation to select promising service arcs used to solve optimally Directed Rural Postman problems. The ex-post refinement tries to improve the solution provided by the matheuristic using a branch-and-cut algorithm. The method gets a quick convergence through the introduction of connectivity cuts that are not guaranteed to be valid inequalities, and thus may exclude integer feasible solutions. All proposed methods have been tested on benchmark instances found in literature and compared to state of the art algorithms. Results show that heuristic methods are extremely effective outperforming existing algorithms. Moreover, our exact method is able to close, in less than one hour, all the 22 benchmark instances that have not been solved to optimality yet.

New results for the Directed Profitable Rural Postman Problem

COLOMBI, Marco;MANSINI, Renata
2014-01-01

Abstract

We study a generalization of the Directed Rural Postman Problem where not all arcs requiring a service have to be visited provided that a penalty cost is paid if a service arc is not crossed. The problem, known as Directed Profitable Rural Postman Problem, looks for a tour visiting the selected set of service arcs while minimizing both traveling and penalty costs. We add different valid inequalities to a known mathematical formulation of the problem and develop a branch-and-cut algorithm that introduces connectivity constraints both in a “lazy” and in a standard way. We also propose a matheuristic followed by an improvement heuristic (final refinement). The matheuristic exploits information provided by a problem relaxation to select promising service arcs used to solve optimally Directed Rural Postman problems. The ex-post refinement tries to improve the solution provided by the matheuristic using a branch-and-cut algorithm. The method gets a quick convergence through the introduction of connectivity cuts that are not guaranteed to be valid inequalities, and thus may exclude integer feasible solutions. All proposed methods have been tested on benchmark instances found in literature and compared to state of the art algorithms. Results show that heuristic methods are extremely effective outperforming existing algorithms. Moreover, our exact method is able to close, in less than one hour, all the 22 benchmark instances that have not been solved to optimality yet.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/210502
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