An Integrated Location Inventory Model for Designing a Supply Chain Network under Uncertainty

作者：Aryanezhad Mir Bahador; Naini Seyed Gholamreza Jalali; Jabbarzadeh Armin^*

来源：Life Science Journal-Acta Zhengzhou University Overseas Edition, 2011, 8(4): 670-679.

• Birth-death process
• genetic algorithm
• location model
• supply chain design model

This paper studies a supply chain design problem with an unreliable supplier and random demand. Due to imperfect performance of the supplier, the quantity of the product received from the supplier may be less than the quantity ordered by distribution centers (DCs). In this system, customers have random demands and the supply chain is flexible in determining which customers to serve. The problem is formulated as a nonlinear integer programming model that simultaneously determines which customers are served, where DCs are located and how DCs are assigned to the customers. The objective of the model is to minimize the total costs including location costs, nonlinear inventory costs, transportation costs, and lost sales costs. In order to solve the model, an effective solution method based on genetic algorithm is developed. Finally, computational results for several instances of the problem are presented to demonstrate the effectiveness of the proposed solution approach. [Mir-Bahador Aryanezhadl, Seyed Gholamreza Jalali Naini, Armin Jabbarzadeh. An Integrated Location Inventory Model for Designing a Supply Chain Network under Uncertainty. Life Science Journal. 2011; 8(4): 670-679] (ISSN: 1097-8135). http://www.lifesciencesite.com.

• 出版日期2011