Journal of Applied Mathematics
Volume 2013 (2013), Article ID 619898, 8 pages
Research Article

Tradeoff Analysis for Optimal Multiobjective Inventory Model

1School of Economics and Management, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China
2Institute of Information and Decision Sciences, National Taipei College of Business, Taipei 10051, Taiwan
3Department of Information Management, Yu Da University, Miaoli 36143, Taiwan
4Department of Accounting Information, National Taipei College of Business, Taipei 10051, Taiwan
5School of Management, Jiangsu University, Zhengjiang, Jiangsu 212013, China

Received 1 February 2013; Accepted 14 April 2013

Academic Editor: Farhad Hosseinzadeh Lotfi

Copyright © 2013 Longsheng Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Deterministic inventory model, the economic order quantity (EOQ), reveals that carrying inventory or ordering frequency follows a relation of tradeoff. For probabilistic demand, the tradeoff surface among annual order, expected inventory and shortage are useful because they quantify what the firm must pay in terms of ordering workload and inventory investment to meet the customer service desired. Based on a triobjective inventory model, this paper employs the successive approximation to obtain efficient control policies outlining tradeoffs among conflicting objectives. The nondominated solutions obtained by successive approximation are further used to plot a 3D scatterplot for exploring the relationships between objectives. Visualization of the tradeoffs displayed by the scatterplots justifies the computation effort done in the experiment, although several iterations needed to reach a nondominated solution make the solution procedure lengthy and tedious. Information elicited from the inverse relationships may help managers make deliberate inventory decisions. For the future work, developing an efficient and effective solution procedure for tradeoff analysis in multiobjective inventory management seems imperative.