Cost Optimization for the Allocation, Production, and Distribution of a Plastic Manufacturing Company Using Integer Linear Programming

Optimizing the allocation of raw materials, production of raw materials to finished products, and the distribution of finished products can be quite difficult especially if the network of suppliers, production plants, and customers is vast. Linear programming (LP) can be utilized to ensure optimality. Specifically, integer linear programming (ILP) is used in this paper. An ILP model was built to determine from which suppliers and how many raw materials from these suppliers should be acquired, how many raw materials each production plant of the company should acquire, how many of the finished goods each production plant should produce, and from which production plants the finished products should be distributed to the customers. The aim of the model is to minimize total cost incurred which is composed of raw material purchase costs, production costs, and transportation costs. Data such as raw material supply, raw material costs, raw material requirements, production capabilities, production costs, raw material and finished product conversions, customer demand, and transportation costs were gathered from the plastic manufacturing company. The software MATLAB was used to determine the optimal solution. It was then determined that the total cost would be minimized from ₱23,615,400 to ₱21,940,000. Through the use of ILP, the total cost was reduced by ₱1,675,400 or 7.09%. (Conversion rate: ₱50 ~ ${\$}$1).

I. Introduction

A plastic manufacturing company is concerned with making its operations cheaper. The company has three plants with injection molding machines that are used to manufacture mainly two products: plastic chairs and plastic drawers. These two products require two types of raw materials which can be acquired from various suppliers. These raw materials are plastic granules and are used to feed the injection molding machine to produce the chairs and drawers. The company has malls and stores as its customers.