Open Access
Issue
RAIRO-Oper. Res.
Volume 55, Number 3, May-June 2021
Page(s) 1523 - 1540
DOI https://doi.org/10.1051/ro/2021071
Published online 08 June 2021
  • H.R.L. Azad and N.S. Boushehri, Billboard advertising modeling by using network count location problem. Int. J. Traffic Transp. Eng. 4 (2014) 146–160. [Google Scholar]
  • S. Banerjee, M.M. Kabir, N.K. Khadem and C. Chavis, Optimal locations for bikeshare stations: a new GIS based spatial approach. Transp. Res. Interdiscip. Perspect. 4 (2020) 100101. [Google Scholar]
  • R. Bekkers and I. Veldhuizen, Geographical differences in blood donation and philanthropy in the Netherlands – what role for social capital? Tijdschr. Econ. Soc. Geogr. 99 (2008) 483–496. [Google Scholar]
  • O. Berman, D. Krass and J. Wang, The probabilistic gradual covering location problem on a network with discrete random demand weights. Comput. Oper. Res. 38 (2011) 1493–1500. [Google Scholar]
  • W. Bielefeld, J.C. Murdoch and P. Waddell, The influence of demographics and distance on nonprofit location. NVSQ 26 (1997) 207–225. [Google Scholar]
  • R. Blanquero, E. Carrizosa and G. Boglárka, Maximal covering location problems on networks with regional demand. Omega 64 (2016) 77–85. [Google Scholar]
  • G. Bramley, N. Dempsey, S. Power, G. Bramley and C. Brown, What is ‘social sustainability’, and how do our existing urban forms perform in nurturing it sustainable communities and green futures, Conference, Bartlett School of Planning, University College London (2006). [Google Scholar]
  • R. Church and C. ReVelle, The maximal covering location problem. Reg. Sci. Assoc. 38 (1974) 101–118. [Google Scholar]
  • A.A. Coco, A.C. Santos and T.F. Noronha, Formulation and algorithms for the robust maximal covering location problem. Electron. Notes in Disc. Math. 64 (2018) 145–154. [Google Scholar]
  • S. Davari, M.H.F. Zarandi and I.B. Turksen, A greedy variable neighborhood search heuristic for the maximal covering location problem with fuzzy coverage radii. Knowl. Based Syst. 41 (2013) 68–76. [Google Scholar]
  • R.Z. Farahani and M. Hekmatfar, Facility Location: Concepts, Models, Algorithms and Case Studies. Springer Science & Business Media (2009). [Google Scholar]
  • G. Geng and R. Wardlaw, Application of multi-criterion decision making analysis to integrated water resources management. Water Resour. Manage. 27 (2013) 3191–3207. [Google Scholar]
  • R. Gupta, S.K. Muttoo and S.K. Pal, Fuzzy c-means clustering and particle swarm optimization based scheme for common service center location allocation. Appl. Intell. 47 (2017) 624–643. [Google Scholar]
  • C.L. Hwang and A.S.M. Masud, Multiple Objective Decision Making – Methods and ipplications: A State-of-the-Art Survey. Springer Science & Business Media 164 (2012). [Google Scholar]
  • C.L. Hwang and K. Yoon, Methods for Multiple Attribute Decision Making (1981) 58–191. [Google Scholar]
  • A. Jahan and K.L. Edwards, A state-of-the-art survey on the influence of normalization techniques in ranking: improving the materials selection process in engineering design. Mater. Des. 1980–2015 65 (2015) 335–342. [Google Scholar]
  • Ö. Kabak and B. Ervural, Multiple attribute group decision making: a generic conceptual framework and a classification scheme. Knowl. Based Syst. 123 (2017) 13–30. [Google Scholar]
  • G. Kannan, A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider. Resour. Conserv. Recycl. 1 (2009) 28–36. [Google Scholar]
  • C. Lee and J. Han, Benders-and-price approach for electric vehicle charging station location problem under probabilistic travel range. Transp. Res. Part B: Methodol. 106 (2017) 130–152. [Google Scholar]
  • T.S. Liou and M.J.J. Wang, Fuzzy weighted average: an improved algorithm. Fuzzy Sets Syst. 3 (1992) 307–315. [Google Scholar]
  • R. Lotfi, Y.Z. Mehrjerdi and N. Mardani, A multi-objective and multi-product advertising billboard location model with attraction factor mathematical modeling and solutions. Int. J. Appl. Logist. (IJAL) 7 (2017) 64–86. [Google Scholar]
  • M. Lwin and I. Phau, Characteristics of charitable donors in Australia recent advances in retailing and services science, Conference Proceedings: Recent Advances In Retailing And Services science(2010). [Google Scholar]
  • J.D. Marx, V.B. Carter, N.K. Khadem and C. Chavis, Factors influencing US charitable giving during the great recession: implications for nonprofit administration. Adm. Sci. 4 (2014) 350–372. [Google Scholar]
  • M.F. Moeen and K.H. Taghizadeh, A new heuristic solution method for maximal covering location-allocation problem with M/M/1 queueing system. J. Sci. Islamic Repub. Iran 23 (2012) 67–75. [Google Scholar]
  • R. Narasimhan, S.K. Talluri, J. Sarkis and A. Ross, Efficient service location design in government services: a decision support system framework. J. Oper. Manage. 23 (2005) 163–178. [Google Scholar]
  • C. Park and S.Y. Sohn, An optimization approach for the placement of bicycle-sharing stations to reduce short car trips: an application to the city of Seoul. Transp. Res. Part A: Policy Pract. 105 (2017) 154–166. [Google Scholar]
  • S.H.R. Pasandideh, S.T.A. Niaki and K. Asadi, Optimizing a bi-objective multiproduct multi-period three echelon supply chain network with warehouse reliability. Expert Syst. App. 42 (2015) 2615–2623. [Google Scholar]
  • N.R. Patel, Locating rural social service centers in India. Manage. Sci. 25 (1979) 22–30. [Google Scholar]
  • M.A. Pereira, L.C. Coelho, L.A. Lorena and L.C. De Souza, Hybrid method for the probabilistic maximal covering location–allocation problem. Comput. Oper. Res. 57 (2015) 51–59. [Google Scholar]
  • M. Pouraliakbari, M. Mohammadi and A. Mirzazadeh, Analysis of maximal covering location-allocation model for congested healthcare systems in user choice environment. Int. J. Ind. Syst. Eng. 28 (2018) 240–274. [Google Scholar]
  • S.U. Rahman and D.K. Smith, Use of location-allocation models in health service development planning in developing nations. Eur. J. Oper. Res. 123 (2000) 437–452. [Google Scholar]
  • A.P. Sargaonkar, B. Rathi and A. Baile, Identifying potential sites for artificial groundwater recharge in sub-watershed of River Kanhan. India. Environ. Earth Sci. 6 (2010) 1–10. [Google Scholar]
  • J.A. Tali, M.M. Malik, S. Divya, A. Nusrath and B. Mahalingam, Location–allocation model applied to urban public services: spatial analysis of fire stations in Mysore urban area Karnataka. India. Int. J. Adv. Res. Dev. 2 (2017) 795–801. [Google Scholar]
  • I. Vinogradova, Multi-attribute decision-making methods as a part of mathematical optimization. Mathematics 7 (2019) 915. [Google Scholar]
  • K. Yao and I. Phau, Who gives the determinants of charitable giving, volunteering, and their relationship (2015). [Google Scholar]
  • E.K. Zavadskas and Z. Turskis, Multiple criteria decision making (MCDM) methods in economics: an overview. Technol. Econ. Dev. Econ. 17 (2011) 397–427. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.