a new model for location-allocation problem within queuing framework

this paper proposes a bi-objective model for the facility location problem under a congestion system. the idea of the model is motivated by applications of locating servers in bank automated teller machines (atms), communication networks, and so on. this model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing framework. we formulate this model with two perspectives simultaneously: (i) customers and (ii) service provider. the objectives of the model are to minimize (i) the total expected travelling and waiting time and (ii) the average facility idle-time. this model represents a mixed-integer nonlinear programming problem which belongs to the class of np-hard problems. in addition, to solve the model, two metaheuristic algorithms including non-dominated sorting genetic algorithms (nsga-ii) and non-dominated ranking genetic algorithms (nrga) are proposed. besides, to evaluate the performance of the two algorithms some numerical examples are roduced and analyzed with some metrics to determine which algorithm works better.