A two-storage multi-item inventory model with hybrid number and nested price discount via hybrid heuristic algorithm

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• 作者：Dipak Kumar Jana ; Barun Das
• 关键词：Two ; storage ; Hybrid number ; K ; release rule ; Nested discount ; Genetic algorithm ; Hybrid heuristic algorithm
• 刊名：Annals of Operations Research
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：248
• 期：1-2
• 页码：281-304
• 全文大小：
• 刊物类别：Business and Economics
• 刊物主题：Operation Research/Decision Theory; Combinatorics; Theory of Computation;
• 出版者：Springer US
• ISSN：1572-9338
• 卷排序：248

文摘

The purpose of this paper is to study a multi-item two warehouse inventory model with a nested discount on unit cost and inventory costs over a fixed time period. The concept of hybrid number and a new type of price discount have been applied in formulating an inventory control system having two separate storage facilities (owned-OW and rented-RW warehouses) due to limited capacity of OW. Here, demand rate is a linear function of selling price and time. The stocks at rented warehouse (RW) are transported to the owned warehouse (OW) following bulk-release rule. So, the mathematical model of the system becomes a constrained non-linear mixed-optimization problem. Here, taking the advantage of the randomness of multi-objective genetic algorithm with varying population (MOGAVP), for the first time, an algorithm has been proposed for the solution of multi-item two-warehouse inventory problems with nested price breaks. The optimum results are compared with MOGAVP and hybrid heuristic algorithm (HA). The optimal shipments, lot size of the two warehouses, shipment size and maximum profit are determined by maximizing the profit function. Finally optimal decision is made using above mentioned MOGAVP. Performance of the proposed MOGAVP on the model with respect to a standard MOGA and HA are compared.