Most of algorithms or logics to solve mathematical problems adopt multiple parameters such as coefficients and thresholds whose values should be carefully selected to enhance the performance. Conventionally, their developers or users tune them by trial and error, where they repeat to apply algorithms or logics with proper parameter values to available input data sets and modify them based on the results. As a result, this tuning process may consume a great deal of energy and not always provide the optimal ones. In this paper, we present a versatile parameter optimization tool to explore optimal values of parameters for various algorithms/logics. We show the effectiveness through applications for the throughput estimation model for wireless local-area networks, with the extension of the model.