A branch-and-cut algorithm for the partitioning-hub location-routing problem

2011 ◽  
Vol 38 (2) ◽  
pp. 539-549 ◽  
Author(s):  
Daniele Catanzaro ◽  
Eric Gourdin ◽  
Martine Labbé ◽  
F. Aykut Özsoy
Keyword(s):  
Branch And Cut ◽  
Hub Location ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

An efficient heuristic for a hub location routing problem

2020 ◽  
Author(s):  
Mustapha Ratli ◽  
Dragan Urošević ◽  
Abdessamad Ait El Cadi ◽  
Jack Brimberg ◽  
Nenad Mladenović ◽  
...  
Keyword(s):  
Hub Location ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

scholarly journals Solving Partitioning-Hub Location-Routing Problem using DCA

2012 ◽  
Vol 8 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Anh Son Ta ◽  
◽  
Le Thi Hoai An ◽  
Djamel Khadraoui ◽  
Pham Dinh Tao ◽  
...  
Keyword(s):  
Hub Location ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

scholarly journals A new formulation and an exact approach for the many-to-many hub location-routing problem

2013 ◽  
Vol 37 (12-13) ◽  
pp. 7465-7480 ◽  
Author(s):  
Ricardo Saraiva de Camargo ◽  
Gilberto de Miranda ◽  
Arne Løkketangen
Keyword(s):  
Hub Location ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Exact Approach ◽  
Location Routing ◽  
The Many ◽  
New Formulation

scholarly journals An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Solution Method ◽  
Programming Model ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

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