Optimizing unprecedented Maximal Covering Location Problem with simulated annealing Algorithm

Author

Rabieyan, Reza ; Esfandiari, Nima

Author_Institution

Dept. of Ind. Eng., Qazvin Islamic Azad Univ., Qazvin, Iran

fYear

2011

fDate

5-7 June 2011

Firstpage

78

Lastpage

82

Abstract

The Maximal Covering Location Problem (MCLP) maximizes the population that has a facility within a maximum travel distance or time. Numerous extensions have been proposed to enhance its applicability, like the probabilistic model for the maximum covering location- allocation with constraint in waiting time or queue length for congested systems with one or more servers per service center. In this research, we present a novel Queuing Location problem that can be determined as MCLP and then we solve this problem with simulated annealing algorithm; the results of solving the problem with the solution algorithms and comparison between them are presented.

Keywords

facility location; queueing theory; set theory; simulated annealing; MCLP optimization; congested systems; maximum covering location allocation; maximum travel distance; probabilistic model; queuing location problem; service center; simulated annealing algorithm; unprecedented maximal covering location problem optimization; waiting time; Annealing; Computational modeling; Europe; Mathematical model; Probabilistic logic; Servers; Simulated annealing;

fLanguage

English

Publisher

ieee

Conference_Titel

Business, Engineering and Industrial Applications (ICBEIA), 2011 International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4577-1279-1

Type

conf

DOI

10.1109/ICBEIA.2011.5994262

Filename

5994262