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All issues Volume 55 (2021) Supplement RAIRO-Oper. Res., 55 (2021) S2055-S2069 References
Free Access
Issue
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
Page(s) S2055 - S2069
DOI https://doi.org/10.1051/ro/2020058
Published online 02 March 2021
  • A. Ahmadi-Javid, E. Amiri and M. Meskar, A profit-maximization location-routing-pricing problem: a branch-and-price algorithm. Eur. J. Oper. Res. 271 (2018) 866–881. [Google Scholar]
  • J. Ahn, O. de Weck, Y. Geng and D. Klabjan, Column generation based heuristics for a generalized location routing problem with profits arising in space exploration. Eur. J. Oper. Res. 223 (2012) 47–59. [Google Scholar]
  • L. Alfandari, Improved approximation of the general soft-capacitated facility location problem. RAIRO:OR 41 (2007) 83–93. [Google Scholar]
  • C. Archetti, F. Carrabs and R. Cerulli, The set orienteering problem. Eur. J. Oper. Res. 267 (2018) 264–272. [Google Scholar]
  • D.G. Baklagis, G. Dikas and I. Minis, The team orienteering pick-up and delivery problem with time windows and its applications in fleet sizing. RAIRO:OR 50 (2016) 503–517. [Google Scholar]
  • R. Baldacci, A. Mingozzi and R. Wolfler Calvo, An exact method for the capacitated location-routing problem. Oper. Res. 59 (2011) 1284–1296. [Google Scholar]
  • S. Barreto, Available at: http://sweet.us.pt/iscf143 (2003). [Google Scholar]
  • S. Barreto, C. Ferreira, J. Paixao and B. Sousa Santos, Using clustering analysis in a capacitated location-routing problem. Eur. J. Oper. Res. 179 (2007) 968–977. [Google Scholar]
  • J.M. Belenguer, E. Benavent, C. Prins, C. Prodhon and R. Wolfler-Calvo, A branch-and-cut method for the capacitated location-routing problem. Comput. Oper. Res. 38 (2011) 931–941. [Google Scholar]
  • N. Bianchessi, R. Mansini and M.G. Speranza, A branch-and-cut algorithm for the Team Orienteering Problem. Int. Trans. Oper. Res. 25 (2018) 627–635. [Google Scholar]
  • M. Boccia, T.G. Crainic, A. Sforza and C. Sterle, Multi-commodity location-routing: flow intercepting formulation and branch-and-cut algorithm. Comput. Oper. Res. 89 (2018) 94–112. [Google Scholar]
  • T. Capelle, C.E. Cortés, M. Gendreau, P.A. Rey and L.-M. Rousseau, A column generation approach for location-routing problems with pickup and delivery. Eur. J. Oper. Res. 272 (2019) 121–131. [Google Scholar]
  • I.M. Chao, B.L. Golden and E.A. Wasil, A fast and effective heuristic for the orienteering problem. Eur. J. Oper. Res. 88 (1996) 475–489. [Google Scholar]
  • W.R. Cherif-Khettaf, M.H. Rachid, C. Bloch and P. Chatonnay, New notation and classification scheme for vehicle routing problems. RAIRO:OR 49 (2015) 161–194. [Google Scholar]
  • C. Contardo, V. Hemmelmayr and T.G. Crainic, Lower and upper bounds for the two-echelon capacitated location-routing problem. Comput. Oper. Res. 39 (2012) 3185–3199. [PubMed] [Google Scholar]
  • Z. Dai, F. Aqlan, K. Gao and Y. Zhou, A two-phase method for multi-echelon location-routing problems in supply chains. Expert Syst. App. 115 (2019) 618–634. [Google Scholar]
  • H. Derbel, B. Jarboui, S. Hanafi and H. Chabchoub, Genetic algorithm with iterated local search for solving a location-routing problem. Expert Syst. App. 39 (2012) 2865–2871. [Google Scholar]
  • M. Drexl and M. Schneider, A survey of variants and extensions of the location-routing problem. Eur. J. Oper. Res. 241 (2015) 283–308. [Google Scholar]
  • T. Drezner, Z. Drezner and D. Zerom, Competitive facility location with random attractiveness. Oper. Res. Lett. 46 (2018) 312–317. [Google Scholar]
  • C. Duhamel, P. Lacomme, C. Prins and C. Prodhon, A GRASP×ELS approach for the capacitated location-routing problem. Comput. Oper. Res. 37 (2010) 1912–1923. [Google Scholar]
  • J.W. Escobar, R. Linfati and P. Toth, A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Comput. Oper. Res. 40 (2013) 70–79. [Google Scholar]
  • K.M. Ferreira and T.A. de Queiroz, Two effective simulated annealing algorithms for the Location-Routing Problem. Appl. Soft Comput. 70 (2018) 389–422. [Google Scholar]
  • D. Gavalas, V. Kasapakis, C. Konstantopoulos, G. Pantziou, N. Vathis and C. Zaroliagis, The eCOMPASS multimodal tourist tour planner. Expert Syst. App. 42 (2015) 7303–7316. [Google Scholar]
  • H. Gavranović and M. Buljubašić, A hybrid approach combining local search and constraint programming for a large scale energy management problem. RAIRO:OR 47 (2013) 481–500. [Google Scholar]
  • B.L. Golden, L. Levy and R. Vohra, The orienteering problem. Nav. Res. Logist. 34 (1987) 307–318. [Google Scholar]
  • A. Gunawan, H.C. Lau and P. Vansteenwegen, Orienteering problem: a survey of recent variants, solution approaches and applications. Eur. J. Oper. Res. 255 (2016) 315–332. [Google Scholar]
  • M. Khorbatly, H. Dkhil, H. Alabboud and A. Yassine, A hybrid algorithm Tabu Search – GRASP for wounded evacuation in disaster response. RAIRO:OR 54 (2020) 19–36. [Google Scholar]
  • G. Kobeaga, M. Merino and J.A. Lozano, An efficient evolutionary algorithm for the orienteering problem. Comput. Oper. Res. 90 (2018) 42–59. [Google Scholar]
  • R. Kohli and R. Krishnamurti, A total-value greedy heuristic for the integer knapsack problem. Oper. Res. Lett. 12 (1992) 65–71. [Google Scholar]
  • G. Laporte, Location-routing problems, edited by B.L. Golden and A.A. Assad. In: Vehicle Routing: Methods and Studies. North-Holland, Amsterdam (1988) 163–198. [Google Scholar]
  • J. Li, P.M. Pardalos, H. Sun, J. Pei and Y. Zhang, Iterated local search embedded adaptive neighborhood selection approach for the multi-depot vehicle routing problem with simultaneous deliveries and pickups. Expert Syst. App. 42 (2015) 3551–3561. [Google Scholar]
  • B. Ludwig, B. Zenker and J. Schrader, Recommendation of personalized routes with public transport connections. Intelligent Interactive Assistance and Mobile Multimedia Computing, edited by D. Tavangarian, T. Kirste and D. Timmermann. In: International Conference, IMC 2009, Rostock-Warnemünde, Germany, November 9–11, 2009. Proceedings. Springer Berlin Heidelberg, Berlin, Heidelberg (2009) 97–107. [Google Scholar]
  • S. Majidi, S.-M. Hosseini-Motlagh, S. Yaghoubi and A. Jokar, Fuzzy green vehicle routing problem with simultaneous pickup – delivery and time windows. RAIRO:OR 51 (2017) 1151–1176. [Google Scholar]
  • F. Malucelli, A. Giovannini and M. Nonato, Designing single origin-destination itineraries for several classes of cycle-tourists. Transp. Res. Proc. 10 (2015) 413–422. [Google Scholar]
  • S.M.H. Manzour-al-Ajdad, S.A. Torabi and S. Salhi, A hierarchical algorithm for the planar single-facility location routing problem. Comput. Oper. Res. 39 (2012) 461–470. [Google Scholar]
  • A. Nadizadeh, The fuzzy multi-depot vehicle routing problem with simultaneous pickup and delivery: formulation and a heuristic algorithm. Int. J. Ind. Eng. Prod. Res. 28 (2017) 325–345. [Google Scholar]
  • A. Nadizadeh and H. Hosseini Nasab, Modelling and solving the capacitated location-routing problem with simultaneous pickup and delivery demands. Int. J. Transp. Eng. 6 (2019) 217–235. [Google Scholar]
  • A. Nadizadeh and B. Kafash, Fuzzy capacitated location-routing problem with simultaneous pickup and delivery demands. Transp. Lett. 11 (2019) 1–19. [Google Scholar]
  • A. Nadizadeh and H.H. Nasab, Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm. Eur. J. Oper. Res. 238 (2014) 458–470. [Google Scholar]
  • A. Nadizadeh, R. Sahraeian, A. Sabzevari Zadeh and S.M. Homayouni, Using greedy clustering method to solve capacitated location-routing problem. Afr. J. Bus. Manage. 5 (2011) 7499–7506. [Google Scholar]
  • A. Nadizadeh, A. Sadegheih and A. Sabzevari Zadeh, A hybrid heuristic algorithm to solve capacitated location-routing problem with fuzzy demands. Int. J. Ind. Math. 9 (2017) 1–20. [Google Scholar]
  • G. Nagy and S. Salhi, Location-routing: issues, models and methods. Eur. J. Oper. Res. 177 (2007) 649–672. [Google Scholar]
  • V.P. Nguyen, C. Prins and C. Prodhon, Solving the two-echelon location routing problem by a GRASP reinforced by a learning process and path relinking. Eur. J. Oper. Res. 216 (2012) 113–126. [Google Scholar]
  • J. Pietz and J.O. Royset, Generalized orienteering problem with resource dependent rewards. Nav. Res. Logist. 60 (2013) 294–312. [Google Scholar]
  • C. Prins, C. Prodhon and R. Wolfler Calvo, Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. Oper. Res. Q. 4 (2006) 221–238. [Google Scholar]
  • C. Prodhon and C. Prins, A survey of recent research on location-routing problems. Eur. J. Oper. Res. 238 (2014) 1–17. [Google Scholar]
  • S. Rath and W.J. Gutjahr, A math-heuristic for the warehouse location–routing problem in disaster relief. Comput. Oper. Res. 42 (2014) 25–39. [Google Scholar]
  • M. Rodrigues de Holanda Maia, A. Plastino and P.H. Vaz Penna, Hybrid data mining heuristics for the heterogeneous fleet vehicle routing problem. RAIRO:OR 52 (2018) 661–690. [Google Scholar]
  • R. Sahraeian and A. Nadizadeh, Using greedy clustering method to solve capacitated location-routing problem. In: XIII Congreso de Ingeniería de Organización. Barcelona (2009) 1721–1729. [Google Scholar]
  • S. Salhi and G.K. Rand, The effect of ignoring routes when locating depots. Eur. J. Oper. Res. 39 (1989) 150–156. [Google Scholar]
  • W. Souffriau, P. Vansteenwegen, J. Vertommen, G.V. Berghe and D.V. Oudheusden, A personalized tourist trip design algorithm for mobile tourist guides. Appl. Artif. Intell. 22 (2008) 964–985. [Google Scholar]
  • P. Vansteenwegen, W. Souffriau and D.V. Oudheusden, The orienteering problem: a survey. Eur. J. Oper. Res. 209 (2011) 1–10. [Google Scholar]
  • E. Yakıcı, Solving location and routing problem for UAVs. Comput. Ind. Eng. 102 (2016) 294–301. [Google Scholar]
  • J. Yang and H. Sun, Battery swap station location-routing problem with capacitated electric vehicles. Comput. Oper. Res. 55 (2015) 217–232. [Google Scholar]
  • Q. Yu, K. Fang, N. Zhu and S. Ma, A matheuristic approach to the orienteering problem with service time dependent profits. Eur. J. Oper. Res. 273 (2019) 488–503. [Google Scholar]
  • V.F. Yu, P. Jewpanya, S.-W. Lin and A.A.N.P. Redi, Team orienteering problem with time windows and time-dependent scores. Comput. Ind. Eng. 127 (2019) 213–224. [Google Scholar]
  • Y. Zare Mehrjerdi and A. Nadizadeh, Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands. Eur. J. Oper. Res. 229 (2013) 75–84. [Google Scholar]
  • Y. Zare Mehrjerdi and A. Nadizadeh, Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands. Int. J. Ind. Eng. Prod. Res. 27 (2016) 1–19. [Google Scholar]
  • S. Zhang, J.W. Ohlmann and B.W. Thomas, A priori orienteering with time windows and stochastic wait times at customers. Eur. J. Oper. Res. 239 (2014) 70–79. [Google Scholar]
  • J. Zhao and V. Verter, A bi-objective model for the used oil location-routing problem. Comput. Oper. Res. 62 (2015) 157–168. [Google Scholar]

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