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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Gouveia, L., Paias, A. & Ponte, M. (N/A). A matheuristic for the traveling salesman problem with positional consistency constraints. International Transactions of Operations Research. N/A
Exportar Referência (IEEE)
L. Gouveia et al.,  "A matheuristic for the traveling salesman problem with positional consistency constraints", in Int. Transactions of Operations Research, vol. N/A, N/A
Exportar BibTeX
@article{gouveiaN/A_1764984162232,
	author = "Gouveia, L. and Paias, A. and Ponte, M.",
	title = "A matheuristic for the traveling salesman problem with positional consistency constraints",
	journal = "International Transactions of Operations Research",
	year = "N/A",
	volume = "N/A",
	number = "",
	doi = "10.1111/itor.70125",
	url = "https://onlinelibrary.wiley.com/journal/14753995"
}
Exportar RIS
TY  - JOUR
TI  - A matheuristic for the traveling salesman problem with positional consistency constraints
T2  - International Transactions of Operations Research
VL  - N/A
AU  - Gouveia, L.
AU  - Paias, A.
AU  - Ponte, M.
PY  - N/A
SN  - 0969-6016
DO  - 10.1111/itor.70125
UR  - https://onlinelibrary.wiley.com/journal/14753995
AB  - We propose a matheuristic for the traveling salesman problem with positional consistency constraints, where we seek to generate a set of routes with minimum total cost, in which the nodes visited in more than one route (consistent nodes) must occupy the same relative position in all routes. The matheuristic is an iterated local search based algorithm that uses a restricted version of the problem under study, where the positions of consistent nodes are fixed, to significantly improve the quality of local optima found by the local search. Computational results show that, for instances with 48–171 nodes and 5 or 10 routes, the matheuristic can obtain, in short computational times, significantly better solutions than an exact method in 10 hours, obtaining optimal or near-optimal solutions for instances where the optimal solution is known.
ER  -