A Multi-Objective Optimization Framework For Strategic Quality, Innovation, And Sustainability Portfolio Management In Modern Enterprises

Abstract

In today's business landscape, many companies are confronted with the challenge of delivering good products, innovative developments, and sustainable solutions in an environment with constrained resources. The existing portfolio management strategies tend to optimize each objective leading to sub-optimal strategic decision making. This study introduces a new multi-objective optimization approach for the strategic portfolio management of quality, innovation and sustainability through the Non dominated Sorting Genetic Algorithm II (NSGA-II) algorithm. The framework combines the quality, innovation, sustainability, risk and resource utilization within a single mathematical optimization model then yields Pareto-optimal portfolio solutions. The results of the simulation proved that the proposed method yielded a Quality Performance Index of 93.4% and an Innovation Capability Score of 91.2% and a Sustainability Performance Index of 94.1%, reduced the portfolio risk by 24.8% and increased the utilization of the resources by 19.6% relative to the conventional weighted-sum optimization method. Besides, the framework converged after 145 optimization iterations to yield stable Pareto solutions in the case of sensitivity analysis of 98.7% solution consistency. The results show the proposed framework as an effective decision-support tool, which balances various strategic goals and increases the competitiveness and sustainable organizational business performance.