With the increasing deployment of the Multi-Path Transmission Control Protocol (MPTCP) in heterogeneous network setups, there is a need to understand how its performance is affected in practice both by traditional factors such as round-trip time measurements, buffer predictive modelling and by calculating the impact factors of network subflows. Studies have shown that path management and packet scheduling have a large effect on overall performance and required limited resources with different congestion control parameters. Unfortunately, most of the previous studies have focused almost exclusively on the improvement of a single parameter, without a holistic view. To deal with this issue effectively, this paper puts forward a Multi-Parameter Comprehensive Optimized Algorithm (MPCOA), which can find the smaller buffer size and select the appropriate congestion control and path management algorithm on the premise of ensuring larger throughput. Experiments of three scenarios show that MPCOA can save the buffer space and subflow resources, and achieve high throughput. Meanwhile, a set of quantitative improvement results given by MPCOA is convenient for us to evaluate the quality of MPTCP network, and provide reference for our ongoing future work, like for 4G/5G, Internet of Things and Star Link networks.