scholarly journals The large scale maximal covering location problem

2011 ◽  
Vol 18 (6) ◽  
pp. 1564-1570 ◽  
Author(s):  
M.H. Fazel Zarandi ◽  
S. Davari ◽  
S.A. Haddad Sisakht
Keyword(s):  
Large Scale ◽  
Location Problem ◽  
Maximal Covering

scholarly journals The large-scale dynamic maximal covering location problem

2013 ◽  
Vol 57 (3-4) ◽  
pp. 710-719 ◽  
Author(s):  
Mohammad Hossein Fazel Zarandi ◽  
Soheil Davari ◽  
Seyyed Ali Haddad Sisakht
Keyword(s):  
Large Scale ◽  
Location Problem ◽  
Maximal Covering

scholarly journals Multi-Period Maximal Covering Location Problem with Capacitated Facilities and Modules for Natural Disaster Relief Services

2021 ◽  
Vol 11 (1) ◽  
pp. 397
Author(s):  
Roghayyeh Alizadeh ◽  
Tatsushi Nishi ◽  
Jafar Bagherinejad ◽  
Mahdi Bashiri
Keyword(s):  
Lower Bounds ◽  
Large Scale ◽  
Location Problem ◽  
Disaster Relief ◽  
Heuristic Method ◽  
Real Life ◽  
Planning Horizon ◽  
Upper Bounds ◽  
Maximal Covering ◽  
Large Scale Problems

The paper aims to study a multi-period maximal covering location problem with the configuration of different types of facilities, as an extension of the classical maximal covering location problem (MCLP). The proposed model can have applications such as locating disaster relief facilities, hospitals, and chain supermarkets. The facilities are supposed to be comprised of various units, called the modules. The modules have different sizes and can transfer between facilities during the planning horizon according to demand variation. Both the facilities and modules are capacitated as a real-life fact. To solve the problem, two upper bounds—(LR1) and (LR2)—and Lagrangian decomposition (LD) are developed. Two lower bounds are computed from feasible solutions obtained from (LR1), (LR2), and (LD) and a novel heuristic algorithm. The results demonstrate that the LD method combined with the lower bound obtained from the developed heuristic method (LD-HLB) shows better performance and is preferred to solve both small- and large-scale problems in terms of bound tightness and efficiency especially for solving large-scale problems. The upper bounds and lower bounds generated by the solution procedures can be used as the profit approximation by the managerial executives in their decision-making process.

scholarly journals The continuous maximal covering location problem in large-scale natural disaster rescue scenes

2020 ◽  
Vol 146 ◽  
pp. 106608
Author(s):  
Pei Yang ◽  
Yiyong Xiao ◽  
Yue Zhang ◽  
Shenghan Zhou ◽  
Jun Yang ◽  
...  
Keyword(s):  
Natural Disaster ◽  
Large Scale ◽  
Location Problem ◽  
Maximal Covering

THE MAXIMAL COVERING LOCATION PROBLEM

2005 ◽  
Vol 32 (1) ◽  
pp. 101-118 ◽  
Author(s):  
RICHARD CHURCH ◽  
CHARLES R. VELLE
Keyword(s):  
Location Problem ◽  
Maximal Covering

Formulation and algorithms for the robust maximal covering location problem

2018 ◽  
Vol 64 ◽  
pp. 145-154 ◽  
Author(s):  
Amadeu A. Coco ◽  
Andréa Cynthia Santos ◽  
Thiago F. Noronha
Keyword(s):  
Location Problem ◽  
Maximal Covering
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