In this research, the problem of location-hierarchical allocation of crowded facilities has been investigated by considering customers’ priority in serving within the framework of queuing systems. The objective functions of the problem are focused on minimizing the total waiting time of customers and minimizing the maximum unemployment of each facility. The problem model is a multi-objective nonlinear programming model, and to evaluate the efficiency of the model, examples in different dimensions have been solved by a multi-objective genetic algorithm (NSGA-II) based on minimal sorting. Since the performance of meta-heuristic algorithms is highly dependent on their parameters, the parameters of this algorithm are adjusted using the Taguchi design. The results show that the establishment of the priority system has reduced the average waiting time of all customers compared to the shift system, so it can be concluded that if in designing hierarchical facilities, the goal is to reduce the waiting time of a particular class of customers, they should Prioritize.
- Crowded Facilities
- Location - Hierarchical Allocation
- NSGA-II Algorithm
- Queue Theory
- Shift System