Informatica

A new heuristic algorithm for solution of bi-objective discrete competitive facility location problems is developed and experimentally investigated by solving different instances of a facility location problem for firm expansion. The proposed algorithm is based on ranking of candidate locations for the new facilities, where rank values are dynamically adjusted with respect to behaviour of the algorithm. Results of the experimental investigation show that the proposed algorithm is suitable for the latter facility location problems and provides good results in sense of accuracy of the approximation of the true Pareto front.

We consider the Multilevel Uncapacitated Facility Location Problem (MLUFLP) and propose a new efficient integer programming formulation of the problem that provides optimal solutions for the MLUFLP test instances unsolved to optimality up to now. Further, we design a parallel Memetic Algorithm (MA) with a new strategy for applying the local search improvement within the MA frame. The conducted computational experiments show that the proposed MA quickly reaches all known optimal and best known solutions from the literature and additionally improves several solutions for large-scale MLUFLP test problems.