Traffic metering at on-ramps in interstate highways has been widely used and led to desirable results. In urban transportation networks when demand reaches network capacity level, traffic metering may also increase network performance efficiency. In this paper, we apply different metering strategies to a case study network to see if they result in a different network operation and potentially a more efficient performance. To make sure if any observed differences in network performance efficiency is due to metering strategies and not due to an inappropriate signal timing, we determine near optimal signal timing of the network by using our Intelligent Dynamic Signal Timing Optimization Program (IDSTOP). IDSTOP incorporates Genetic Algorithms (GAs) with microscopic traffic simulation to find near-optimal signal timing parameters of the network. Our results showed that letting all traffic enter the network or metering a large portion of the traffic are not the best options. Instead metering around 20% of the traffic resulted in the best network performance in terms of average delay (16% reduction compared to no metering and 17% reduction compared to extremely heavy metering strategies), network throughput (18% increase compared to heavy metering), and average travel time (14% reduction compared to no metering and 10% reduction compared to heavy metering). Our findings suggested that in an urban network, there is an optimal point that sending more vehicles into the network than that deteriorates network performance efficiency.