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In the recent technological era, advancement in the application allows faster transmission of data massively over the network, and it leads to the emergence of challenges related to high-speed networks (HSN's). With limitations over the congestion control mechanism, the transmission control protocol mechanism no longer offers support for HSN, and it eventually fails to utilize the resource available. Hence, it is necessary to adopt high-speed variants of congestion control mechanism that offers solution related to massive data transmission, bandwidth utilization and congestion. In this paper, an improvised virtual queue (IVQ) algorithm is adopted to have control over all these three constraints. By selecting all these three constraints, we model a multi-objective optimization process embedded with the IVQ algorithm to maintain a trade-off between the constraints and offer effective congestion control over HSN. The study performs simulations in order to measure the effectiveness of properties of multi-objective optimization-based IVQ. The simulation confirms the improvements over existing congestion control mechanisms like the double index random early detection (DI-RED) model, dynamic random early drop (DRED), and random early detection (RED) in terms of network throughput, delay, packet drop rate etc.