Optimizing Product Attributes Leadership Strategy Using GeneticAlgorithm and Deep LearningCase Study : Electric Vehicle Development

Car manufacturers face challenges in optimizing platform and portfolio management to meetevolving consumer demands and regulatory requirements. This article examines the combineduse of Genetic Algorithms (GAs) and Deep Learning (DL) for optimizing product attributes innext-generation electric vehicles (EVs). By leveraging data science, automakers gain insightsinto consumer preferences and market trends to enhance features like battery life, chargingspeed, safety, and comfort while balancing cost and manufacturability. The proposedframework integrates predictive modeling with evolutionary algorithms to support data-drivendecision-making. This approach fosters competition, customer satisfaction, and innovation inthe automotive sector, enabling manufacturers to create products that align with consumerexpectations and market demands, ultimately enhancing their competitive advantage.

کلیدواژه ها:

Optimization Strategy ، Attributes management ، deep learning models ، Multi ObjectiveGenetic Algorithm ، Python