Using genetic algorithm to determine the optimal order quantities for multi-item multi-period under warehouse capacity constraints in kitchenware manufacturing

International Conference on Informatics, Technology and Engineering 2017

计算机科学

Saraswati, D.^1 ; Sari, D.K.^1 ; Johan, V.^1

Industrial Engineering Department, Trisakti University, Jakarta, Indonesia^1

关键词: Economic order quantity models;    Holding costs;    Inventory costs;    Optimal order quantity;    Ordering cost;    Production requirements;    Purchasing costs;    Warehouse capacity;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/245/1/012020/pdf
DOI  :  10.1088/1757-899X/245/1/012020

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The study was conducted on a manufacturer that produced various kinds of kitchenware with kitchen sink as the main product. There were four types of steel sheets selected as the raw materials of the kitchen sink. The problem was the manufacturer wanted to determine how much steel sheets to order from a single supplier to meet the production requirements in a way to minimize the total inventory cost. In this case, the economic order quantity (EOQ) model was developed using all-unit discount as the price of steel sheets and the warehouse capacity was limited. Genetic algorithm (GA) was used to find the minimum of the total inventory cost as a sum of purchasing cost, ordering cost, holding cost and penalty cost.