This study proposes a decision support methodology based on bidirectional artificial neural networks to resolve the trade-off between short-term and long-term strategies that arises during the formulation of strategic management plans. Short-term strategy was limited to short-term production planning using linear programming, while for long-term strategy, bidirectional artificial neural networks called NNSP (Neural Network for Strategic Positioning) and NNSA (Neural Network for Strategic Action) were applied based on the BCG model and the Growth/Gain model. In cases where short-term strategy formulation through optimization models is infeasible, this study proposes NNAOC (Neural Network for Adaptive Optimal Control) to address such situations. As a prototype for implementing the proposed methodology, a decision support system called STRADSS was designed for effective strategic management formulation. The experiment was conducted using data from a Korean cosmetics company, and the results were validated by demonstrating a 17-step mechanism for resolving trade-offs between long-term and short-term strategies.