This paper focuses on improving the supply chain in the beauty product industry using optimized logistics. The goal is to run the supply chain efficiently while maximizing profits and minimizing costs. To address this challenge, the paper proposes integrating innovative technologies and data-driven decision-making. A key part of the approach is using the NSGA-II (Non-dominated Sorting Genetic Algorithm II) multi-objective optimization algorithm. The model considers various factors like profit maximization, cost reduction, product lines, plant and delivery locations, suppliers, routes, and transportation modes. The goal is to develop a supply chain model that maximizes profit and minimizes cost, providing an optimal solution for supply chain management in the beauty industry. This study contributes to supply chain management by presenting a realistic model for optimizing beauty product supply chains through logistics. As such, this study provides an invaluable contribution to knowledge in the field of supply chain management by presenting a realistic model for optimizing supply chains through logistics. It does highlight the importance of incorporating modern technologies into the operations for superior performance and strategic advantages, among others.