AGGREGATE PLANNING USING MIXED INTEGER PROGRAMMING: A FRUIT JUICE CONCENTRATED FACTORY CASE STUDY

摘要

The case study is a newly opened fruit juice concentrated factory. Three different products have been launched to serve both domestic and international markets. For its inbound logistics, it receives fresh fruits from local growers. As the fresh fruits are seasonal, its prices and quantities are highly fluctuated. A cold storage is then used to freeze and store the fruits during their peak periods in order to reduce risks of fruit shortages and high prices in off peak periods. Storaging costs of fresh fruits are, however, substantial. To produce the finished products, Clean-in-Place (CIP) is being managed before changing the product lines and it takes 3 days for each cleaning or setup. After the production process, the finished products are stocked in its warehouse no more than 2 months as its clients require the products to be 80% viable of its shelf life. Aggregate planning is then needed to match demand with supply of the case study while minimising total operating costs including purchasing cost, raw material inventory cost, semi-product cost, finished inventory cost, setup cost and labour cost. Mixed integer programming is used to find the optimal decision variables that are purchasing volumes, semi-product volumes, production volumes, and setup decisions.