TY - GEN
T1 - A new randomized procedure to solve the location routing problem
AU - Quintero-Araujo, Carlos L.
AU - Juan, Angel A.
AU - Caballero-Villalobos, Juan P.
AU - Montoya-Torres, Jairo R.
AU - Faulin, Javier
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - The Location Routing Problem (LRP) is one of the most important challenging problems in supply chain design since it includes all decision levels in operations management. Due to its complexity, heuristics approaches seem to be the right choice to solve it. In this paper we introduce a simple but powerful approach based on biased randomization techniques to tackle the capacitated version of the LRP. Preliminary tests show that near-optimal or near-BKS can be found in a very short time.
AB - The Location Routing Problem (LRP) is one of the most important challenging problems in supply chain design since it includes all decision levels in operations management. Due to its complexity, heuristics approaches seem to be the right choice to solve it. In this paper we introduce a simple but powerful approach based on biased randomization techniques to tackle the capacitated version of the LRP. Preliminary tests show that near-optimal or near-BKS can be found in a very short time.
KW - Biased randomization
KW - Heuristics
KW - Location routing problem
UR - http://www.scopus.com/inward/record.url?scp=85044037426&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-75792-6_18
DO - 10.1007/978-3-319-75792-6_18
M3 - Conference contribution
AN - SCOPUS:85044037426
SN - 9783319757919
T3 - Advances in Intelligent Systems and Computing
SP - 247
EP - 254
BT - Applied Mathematics and Computational Intelligence, 2015
A2 - Merigó, José M.
A2 - Verma, Rajkumar
A2 - Gil-Lafuente, Anna M.
A2 - Dass, Bal Kishan
PB - Springer Verlag
T2 - 24th International Conference of the Forum for Interdisciplinary Mathematics, FIM 2015
Y2 - 18 November 2015 through 20 November 2015
ER -