TY - JOUR
T1 - The large-scale dynamic maximal covering location problem
AU - Fazel Zarandi, Mohammad Hossein
AU - Davari, Soheil
AU - Haddad Sisakht, Ali
N1 - cited By 37
PY - 2013
Y1 - 2013
N2 - Most of the publications regarding the maximal covering location problem (MCLP) address the case where the decision is to be made for one period. In this paper, we deal with a rather untouched version of MCLP which is called dynamic MCLP (DMCLP). In order to solve this problem, a simulated annealing (SA) has been presented. The proposed solution algorithm is capable of solving problems with up to 2500 demand nodes and 200 potential facilities with a fair amount of exactness. Our experiments showed that the proposed approach finds solutions with errors less than one percent.
AB - Most of the publications regarding the maximal covering location problem (MCLP) address the case where the decision is to be made for one period. In this paper, we deal with a rather untouched version of MCLP which is called dynamic MCLP (DMCLP). In order to solve this problem, a simulated annealing (SA) has been presented. The proposed solution algorithm is capable of solving problems with up to 2500 demand nodes and 200 potential facilities with a fair amount of exactness. Our experiments showed that the proposed approach finds solutions with errors less than one percent.
U2 - 10.1016/j.mcm.2012.07.028
DO - 10.1016/j.mcm.2012.07.028
M3 - Article
SN - 0895-7177
VL - 57
SP - 710
EP - 719
JO - Mathematical and Computer Modelling
JF - Mathematical and Computer Modelling
IS - 3-4
ER -