Application and Algorithm Implementation of Multi Objective Linear Programming in Enterprise Cost Control

As a key link connecting production and market, raw material ordering and transportation not only directly affect the continuous operation capability of the production line, but also profoundly impact the cost control and profit margin of enterprises. In the practice of enterprise management, cost control is one of the core strategies to enhance competitiveness. Multi objective linear programming (MOLP), as an advanced mathematical optimization tool, has shown great potential in the field of cost control due to its ability to simultaneously handle multiple conflicting objectives. This article delves into the specific application of MOLP in enterprise cost control, especially in the fields of raw material ordering and transportation, and innovatively proposes a MOLP solution that integrates artificial intelligence (AI) algorithms. This algorithm utilizes AI algorithms to accurately predict raw material demand trends, dynamically adjust ordering strategies and transportation plans, thereby ensuring supply chain resilience while minimizing ordering and transportation costs. The experimental results show that the algorithm not only significantly improves the accuracy of cost control, but also effectively shortens the turnover time of raw materials, enhances the market response speed and overall operational efficiency of the enterprise.