Abstract

This study conducts an in-depth analysis of the short-term variable transportation and warehousing costs at the Horace Plant (HP). The primary goal is to develop cost-saving strategies that enhance operational efficiency while reducing overall costs. The analysis focuses on three main cost components: trucking costs, pallet movement costs, and warehousing costs, which are incurred during shipments between suppliers, warehouses, and production facilities, as well as the movement and storage of raw materials and components in a short horizon. The study employs Linear Programming (LP) techniques, specifically a Multistage Multi-echelon Multiproduct Mixed Integer Linear Programming (MILP) model, to capture the complexity of Cosmetics Company's supply chain network. The model, including multiple products, suppliers, warehouses, production warehouses, and periods, offers a robust framework for optimization, instilling confidence and reassurance about its effectiveness in supply chain management. Results from the model reveal cost-saving opportunities and operational improvements. Sensitivity analysis provides insights into key cost drivers and potential areas for cost reduction. The practical application of this study lies in its ability to offer real-time, actionable insights for daily supply chain operations, which is crucial for handling demand fluctuations and ensuring cost efficiency in the beauty industry. The study enhances visibility into goods flow and potential short-term shortages by providing deeper managerial insights into the optimal routing and storage of pallets. This supports strategic and tactical planning, driving continuous improvement in supply chain performance and instilling a sense of optimism about the future of supply chain management. Ultimately, the study demonstrates the practical benefits of advanced optimization models in complex, dynamic environments, contributing valuable insights to the field of supply chain management.