In this paper we examine five different strategies for limiting the local search neighborhoods in the context of vehicle routing problems. The vehicle routing problem deals with the assignment of a set of transportation orders to a fleet of vehicles, and the sequencing of stops for each vehicle to minimize transportation costs. The examined strategies are applied to four standard neighborhoods and implemented in a recently suggested powerful memetic algorithm. Experimental results on 26 well-known benchmark problems indicate significant speedups of almost 80% without worsening the solution quality. On the contrary, in 12 cases a new best-known solution was obtained.