摘要
构建了一种基于联合补货策略的配送中心选址-库存集成优化新模型,该模型允许存在瑕疵品并导致缺货。设计了一种改进的自适应混合差分蛙跳算法(Adaptive Hybrid Differential Frog Leaping Algorithm, AHDFLA),该算法将差分进化算法的变异操作与蛙跳算法的寻优操作相结合,同时对三种局部寻优策略进行改进,最后增加审判操作来综合提高原始蛙跳算法的收敛速度和全局寻优能力。进而采用AHDFLA算法对该模型进行求解,最后通过对算例中部分参数进行敏感性分析,得出不同参数对总成本的影响,可为企业运营管理提供科学的决策参考。
The joint replenishment problem (JRP) is the multi-item inventory problem of coordinating the replenishment of a group of items that may be jointly ordered from a single supplier. The cost of placing an order contains two parts: a major ordering cost and a minor ordering cost. The major ordering cost is independent of the number of items ordered and is a fixed cost which can be shared by these items in every order with the joint replenishment policy. So the total cost can be significantly reduced. The academic value and applicability of JRPs are widely accepted. To further improve its practicability, the integrated optimization of location-inventory-problem (LIP) based on joint replenishment policy is a very effective way. As to routine operation management for enterprises, the defective products are inevitable because of uncertain factors such as the imperfect technology level and improper transportation and storage mode. So enterprises have to face the dilemma of shortage. However, the integrated research of the joint replenishment and LIP with defective items does not exist. So a new and integrated LIP using joint replenishment policy (JR-LIP) with imperfect items is proposed in this study. The objective is to minimize the total cost (TC) including the construction cost of distribution centers (DCs), transportation costs from DCs to customers, and routine joint replenishment costs. Deterministic JRP is an NP-hard problem. The JR-LIP model becomes more complex when the location decision is considered simultaneously;it is a more challenging NP-hard problem to be solved. However, the traditional approaches such as enumeration method, heuristic, and genetic algorithm have some defects which are hard to be overcome. So an improved adaptive hybrid differential frog leaping algorithm (AHDFLA) is developed which combined the mutation of the differential evolution algorithm (DE) with the optimization-oriented operation of a shuffled frog leaping algorithm (SFLA). Three local search strategies are modified simultaneously, and trial operation is adopted to improve the convergence speed and global search ability of the original SFLA. Then AHDFLA is utilized to solve the proposed JR-LIP model. The results of the experiment show that the AHDFLA outperforms the original SFLA, the improved SFLA, and adaptive DE. The global optimization ability and stability of AHDFLA are improved. To discuss the influence of parameters on the total cost, a sensitivity analysis is further conducted which could provide useful managerial insights for better operations management. The results show that:(a) when the demand fluctuates within 50%, its impact on TC is still very small;(b) the construction cost of DCs has great impact on TC;(c) the impact of changed major ordering cost on the location decision of DCs is small;and (d) the minor ordering cost and inventory holding cost only have weak impact on TC.
作者
王林
冯俊翔
张金隆
WANG Lin;FENG Jun-xiang;ZHANG Jin-long(School of Management, Huazhong University of Science & Technology, Wuhan 430074,China)
出处
《管理工程学报》
CSSCI
CSCD
北大核心
2019年第2期180-187,共8页
Journal of Industrial Engineering and Engineering Management
基金
国家自然科学基金资助项目(71531009
71371080)
教育部人文社会科学研究规划基金资助项目(15YJA630095)
关键词
选址-库存
联合采购
瑕疵品
蛙跳算法
差分进化
Location-inventory
Joint replenishment
Imperfect items
Shuffled frog leaping algorithm
Differential evolution
