The work deals with a real muti-objective optimization problem in logistics.
Two methods are proposed and analyzed.
The first one is based on MOAMP, a Tabu Search strategy for multi-objective optimization problems.
The second one is based on NSGA-II, a very well-known multi-objective genetic algorithm.
The results of computational experiences show the best performance of MOAMP-based method.