A multi-product batch ordering EOQ model with storage capacity constraint: an application of soft computing in inventory management
A multi-product economic-order-quantity inventory problem under batch ordering with storage capacity constraint is revealed to be a multivariate nonlinear integer programming problem.The retailer decides how many batches to be in an order and how many the maximum backorder level should be for each kind of products, to minimize the total inventory cost of all products.An ant colony optimization algorithm is used to solve this problem, in which a specially designed search space is built to match the decisions structure.A modification of the models constraints is carried out to narrow the search space, resulting in shorter running time and quicker convergences.A genetic algorithm is also employed as a comparison.Furthermore, a combinational approach of ant colony optimization and genetic algorithm, namely ACO-GA method, is proposed.Finally, a numerical example is presented and proves the proposed method helpful in solving this problem.
economic order quantity multi-product capacity constraint multivariate nonlinear integer programming ant colony optimization genetic algorithm
Yong-mei LIU Bo KUANG
School of Business, Central South University, Changsha, China
国际会议
The 5th International Conference on Logistics and Supply Chain Management 2015(第五届物流工程与供应链管理国际研讨会)
长沙
英文
152-161
2015-12-01（万方平台首次上网日期，不代表论文的发表时间）