Formulations and exact algorithms for the distance-constrained generalized directed rural postman problem
Author(s) -
Thais Ávila,
Ángel Corberán,
Isaac Plana,
José M. Sanchis
Publication year - 2015
Publication title -
euro journal on computational optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.95
H-Index - 14
eISSN - 2192-4414
pISSN - 2192-4406
DOI - 10.1007/s13675-015-0053-8
Subject(s) - traverse , vehicle routing problem , automatic meter reading , routing (electronic design automation) , computer science , set (abstract data type) , arc routing , algorithm , extension (predicate logic) , constraint (computer aided design) , metre , series (stratigraphy) , mathematical optimization , mathematics , telecommunications , wireless , computer network , geography , paleontology , physics , geometry , geodesy , astronomy , biology , programming language
The generalized directed rural postman problem is an arc routing problem with many interesting real-life applications, such as routing for meter reading. In this application, a vehicle with a receiver travels through a series of neighborhoods. If the vehicle gets closer than a certain distance to a meter, the receiver is able to record the gas, water, or electricity consumption. Therefore, the vehicle does not need to traverse every street, but only a few, to get close enough to each meter. We study an extension of this problem in which a fleet of vehicles is available. Given the characteristics of the mentioned application, the vehicles have no capacities but there is a maximum distance (or time) constraint all of them have to satisfy. We introduce four formulations for this problem, propose some families of valid inequalities, and present four branch-and-cut algorithms for its solution. The formulations and the algorithms are compared on a large set of instances.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom