Developing a Strategic Approach to Optimizing Product Portfolio in the Automotive Industry

In the automotive industry, effective portfolio management is essential for optimizing resource allocation, managing risks, and enhancing financial performance. This article introduces an integrated optimization framework that utilizes the Markowitz model alongside multi-disciplinary optimization approaches to improve decision-making in portfolio management. By applying advanced optimization methodologies, companies in the automotive sector can devise data-driven strategies that aim to maximize returns and minimize risks, thereby gaining a competitive edge. The article outlines a comprehensive methodology for implementing this integrated optimization framework using Python, which includes steps for data preprocessing, model development, performance analysis, and practical execution. Empirical results from real-world datasets highlight the success of the proposed framework in refining portfolio management practices within the automotive industry, demonstrating its effectiveness in addressing the complex dynamics of portfolio optimization.

Keywords:

Portfolio Management , Platform , Markowitz Model , Multi-Discipline Optimization , Optimization Techniques