Application of robust optimization in capacitated maximal covering location problem

In the real world, uncertainty is an inseparable component in many problems and there is a growing interest to have robust solutions specially for problems with uncertain parameters. In this research, we use robust optimization in the capacitated maximal covering location problem. To come close to reality, we have considered capacity constraint for facilities and customer's demands as an uncertain parameter. A scenariobased approach is adopted to cope with the uncertainty of demands. To solve the model, we have used CPLEX solver and Tabu search algorithm for small and medium sizes, respectively. The efficiency of this algorithm is analyzed and Sensitivity analysis has been conducted to determine the behavior of model with various coverage radiuses and capacities. Finally, the trade-off between solution robustness and model robustness has been analyzed.