Two-warehouse inventory model for non-instantaneous deteriorating items with stock-dependent demand and inflation using particle swarm optimization

被引：0
作者：
Sunil Tiwari
Chandra K. Jaggi
Asoke Kumar Bhunia
Ali Akbar Shaikh
Mark Goh
机构：
[1] University of Delhi,Department of Operational Research, Faculty of Mathematical Sciences, New Academic Block
[2] National University of Singapore,NUS Business School and the Logistics Institute
[3] The University of Burdwan,Asia Pacific
[4] Tecnológico de Monterrey,Department of Mathematics
来源：
Annals of Operations Research | 2017年 / 254卷
关键词：
Inventory; Non-instantaneous deterioration; Partial backlogging; Stock-dependent demand; Inflation; Particle swarm optimization; 90B05;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We investigate a two-warehouse inventory model for non-instantaneous deteriorating items with partial backlogging and stock-dependent demand under inflationary conditions. Shortages are allowed. The backlogging rate is variable and depends on the waiting time for the next replenishment. This paper seeks to determine an optimal replenishment policy that minimizes the present value of the total cost per unit time. The necessary and sufficient conditions for the existence and uniqueness of the optimal solution are found. The corresponding problems are formulated and solved with particle swarm optimization. Numerical experimentation and post-optimality analysis are conducted.
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页码：401 / 423
页数：22
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