A single-facility competitive location problem in the plane based on customer choice rules

2020 ◽  
Vol 2 (4) ◽  
pp. 323-336
Author(s):  
Hongguang Ma ◽  
Xiaoyu Guan ◽  
Liang Wang
2017 ◽  
Vol 78 ◽  
pp. 305-315 ◽  
Author(s):  
José Fernández ◽  
Boglárka G.- Tóth ◽  
Juana L. Redondo ◽  
Pilar M. Ortigosa ◽  
Aránzazu Gila Arrondo

2020 ◽  
pp. 1248-1271
Author(s):  
Seda Tolun ◽  
Halit Alper Tayalı

This chapter focuses on available data analysis and data mining techniques to find the optimal location of the Multicriteria Single Facility Location Problem (MSFLP) at diverse business settings. Solving for the optimal of an MSFLP, there exists numerous multicriteria decision analysis techniques. Mainstream models are mentioned in this chapter, while presenting a general classification of the MSFLP and its framework. Besides, topics from machine learning with respect to decision analysis are covered: Unsupervised Principal Components Analysis ranking (PCA-rank) and supervised Support Vector Machines ranking (SVM-rank). This chapter proposes a data mining perspective for the multicriteria single facility location problem and proposes a new approach to the facility location problem with the combination of the PCA-rank and ranking SVMs.


2019 ◽  
Vol 20 (2) ◽  
pp. 367-393 ◽  
Author(s):  
Vladimir Marianov ◽  
H. A. Eiselt ◽  
Armin Lüer-Villagra

2011 ◽  
Vol 31 (1) ◽  
pp. 282-291 ◽  
Author(s):  
Rafael Suárez-Vega ◽  
Dolores R. Santos-Peñate ◽  
Pablo Dorta-González ◽  
Manuel Rodríguez-Díaz

2008 ◽  
Vol 190 (1) ◽  
pp. 79-89 ◽  
Author(s):  
M. Zaferanieh ◽  
H. Taghizadeh Kakhki ◽  
J. Brimberg ◽  
G.O. Wesolowsky

2015 ◽  
Vol 16 (2) ◽  
pp. 287-299 ◽  
Author(s):  
Dongyan Chen ◽  
Chan He ◽  
Senlin Wu

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