A hybrid artificial bee colony for disruption in a hierarchical maximal covering location problem

• A hybrid artificial bee colony (ABC) is designed to solve reliable hierarchical maximal covering location problem.
• We hybridize the ABC with 2-opt as a local search to find the local optimum in each iteration.
• The algorithm uses the current solutions based on their fitness to generate new solution with higher efficiency.
• The proposed algorithm is capable of finding well-enough solutions for the large-scale problems in a reasonable time.
• We also investigate application of the model and solution technique on a real-life case study.

In traditional facility location problems, it is assumed that facilities would work under any condition. But in the real-world applications, facilities may fail due to disasters such as congestion, earthquakes, floods and adverse weather conditions. Therefore, it is of great importance to develop models which work not only in normal conditions but also after a disruption; applying this concept to traditional facility location problem ends up to reliable facility location problem. In this paper, possibility of failure for facilities is considered and a model is developed in which a hierarchy of facilities are located in order to maximize the total covered demand. This model has application in different areas such as health care and solid waste management systems. Then a hybrid artificial bee colony (HABC) algorithm is presented to solve the model efficiently. The algorithm is hybridized with 2-opt as a local search. Moreover, the algorithm uses the current solutions based on their fitness to generate new ones, which helps the algorithm work more efficiently. The effectiveness of the proposed algorithm is tested via comparing the results with the exact solutions obtained from small-size problems. Finally, after validation, the algorithm is tested over a real-life case example.