Open AccessOptimization of the Replenishment Strategy for the Supplier Based on Genetic Algorithm
Author(s) -
Ke Qing Zhu,
Hengshan Wang,
Kong Yuan-yuan,
Sheng Li
Publication year - 2010
Publication title -
international journal of business and management
Language(s) - English
Resource type - Journals
eISSN - 1833-8119
pISSN - 1833-3850
DOI - 10.5539/ijbm.v6n1p218
Subject(s) - stackelberg competition , genetic algorithm , interval (graph theory) , mathematical optimization , supply chain , minification , computer science , operations research , economic order quantity , order (exchange) , business , microeconomics , economics , mathematics , marketing , finance , combinatorics
In the supply chain management, the supplier can reduce its total cost by providing price discounts to restrict the retailers’ replenishment intervals to multiples of a common replenishment interval. In order to accomplish this purpose, supplier often determined a price discount that all the retailers can accept. After the cost of the supplier was further considered, a better price discount was designed, which can meet all the retailers’ requirements to maximize their benefits. And a new supplier’s minimization problem model based on stackelberg game was designed also. Then a genetic algorithm is used to solve the supplier’s replenishment model. Experiment results of the genetic algorithm demonstrated the feasibility and the effectiveness of the strategy