A bi-level inventory replenishment strategy using clustering genetic algorithm. (2015)

• Record Type: Journal Article
• Authors: Lee, Ming-Chang; Wee, Hui-Ming; Wu, Simon; Wang, C. Edward; Chung, Rih-Lung
• Is Part Of: European journal of industrial engineering. Volume 9:Number 6(2015)
• Page Start: 774
• Page End: 793
• Publication Date: 2015
• Subjects: bi-level programming -- clustering algorithms -- genetic algorithms -- vendor-buyer inventory replenishment -- inventory management -- modelling -- purchasing cost -- market price; Industrial engineering -- Europe -- Periodicals; 658.50094
• Languages: English
• ISSNs: 1751-5254

Abstract

Even though bi-level strategy has many real life applications, it has not received very much attention in the inventory management literature. A typical bi-level strategy is when an enterprise has to react to a more powerful decision-making agency (a dominant leader) such as the government. In this paper, we formulate and solve a single vendor-buyer inventory replenishment problem using a bi-level programming technique. The two scenarios considered are: 1) the supplier as a dominant leader; 2) the buyer as a dominant leader. A bi-level clustering genetic algorithm is utilised to solve the problem. We implement a numerical experiment using the data from a reference with integrated replenishment policy model and compared the performance of our model and the reference model. The computational results show that the net profit of the vendor and buyer under the bi-level strategy is higher than that under the integrated replenishment policy. We also show that the performance between the bi-level strategy and the integrated replenishment policy is sensitive to the purchasing cost and the market price. [Received 15 April 2012; Revised 20 June 2013; Revised 31 January 2014; Revised 26 July 2014; Accepted 27 October 2014]