Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse

The paper presents strategies optimization for an existing automated warehouse located in a steelmaking industry. genetic algorithms are applied to this purpose and three different popular algorithms capable to deal with multi-objective optimization are compared. the three algorithms, namely the niched pareto genetic algorithm, the non-dominated sorting genetic algorithm 2 and the strength pareto genetic algorithm 2, are described in details and the achieved results are widely discussed; moreover several statistical tests have been applied in order to evaluate the statistical significance of the obtained results.