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This paper investigates the impact of several routing strategies on minimization of the travel-time for pickers in a manual warehouse. Many solutions have been proposed in literature over the last years, however, just a few authors really compare them on equal terms in order to carry out a proper comparison. In this work, three well-known heuristic strategies (ie S-Shape, Largest Gap, and Combined) are firstly compared to each other and then with two metaheuristic algorithms owning to swarm intelligence family (ie Ant Colony Optimization and Particle Swarm Optimization). Firstly, an empirical study has been made to find out the best setting for meta-heuristics’ parameters. Then, a discrete event simulation model has been developed by using both Python© and Cython© programming languages, and the analyzed strategies have been compared under several storage assignment policies.