A mixed integer linear programming model for the multi-item uncapacitated lot-sizing problem: a case study in the trailer manufacturing industry. (2017)

• Record Type: Journal Article
• Authors: Mohammadi, Maryam; Shekarian, Ehsan
• Is Part Of: International journal of multivariate data analysis. Volume 1:Number 2(2017)
• Page Start: 173
• Page End: 199
• Publication Date: 2017
• Subjects: mixed integer programming -- uncapacitated lot-sizing -- demand forecasting -- price estimation -- safety stock -- material requirements planning -- MRP -- optimum order quantity -- cost minimisation -- LINGO -- GAMS -- trailer manufacturer
• Languages: English
• ISSNs: 2396-8311

Abstract

In this paper, a mixed integer linear programming model for the multi-item uncapacitated lot-sizing problem is presented. The considered factors for formulating the proposed model are the monthly demand of the selected product from the case study company, type of parts used in the product and their consumption coefficients based on the bill of materials, lead time to receive parts from outsourcing suppliers, the costs of ordering, purchasing, and holding, and the amount of safety stock for each part. Accordingly, several forecasting techniques are tried to determine future demands. The prices of the selected parts are estimated using linear regression method. The optimal safety stock for each part is calculated based on variance in demand, lead time and the target service level. Material requirements planning are also performed to obtain the economic purchasing schedule of parts. LINGO and GAMS software are used to solve and validate the suggested model respectively. The results show that the proposed model can find the optimum order quantity for each part per period, which minimises the total cost.