Artificial Intelligence in Market Segment Portfolio for Profit Maximization

Abstract

This paper proposes an approach to select a market segment portfolio to maximize overall profit. The study first uses artificial intelligence algorithms to select the market segments with high profitability. The mathematical programming model is then used to identify the most profitable market segment portfolio. The single-objective programming model is used to find the optimal profit for the baseline condition, and a sensitivity analysis is performed to understand the impact of the variable changes on the results. Then, a multi-objective programming model helps to identify the best profit when the evaluated items reach extreme values. A sensitivity analysis is conducted to reveal the impact of the variable changes on the results. The above results are compared with those of the scoring method. It is found that the artificial intelligence algorithm combined with mathematical programming models can indeed find the market segmentation portfolio with better profits than the conventional methods.