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Optimizing unprecedented Maximal Covering Location Problem with simulated annealing Algorithm

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.