Optimizing of Multi-objective Inventory Model by Different Fuzzy Techniques

被引:0
|
作者
Mishra U. [1 ,2 ]
Waliv R.H. [3 ]
Umap H.P. [4 ]
机构
[1] Department of Business Administration, Soochow University, 56 Section 1, Kuei-yang Street, Taipei
[2] Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore
[3] Kisan Veer Mahavidyalaya, Wai, Maharashtra
[4] Yashwantrao Chavan Institute of Science, Satara, Maharashtra
关键词
Fuzzy non-linear programming (FNLP); Intuitionistic fuzzy optimization (IFO); Multi-objective inventory model;
D O I
10.1007/s40819-019-0721-0
中图分类号
学科分类号
摘要
A multi-objective, multi item inventory model is constructed for deteriorating items where the demand is considered as exponential time function under limited storage space as well as budget. By using Fuzzy non linear programming (FNLP) and Intutionistic fuzz optimization (IFO) techniques results are obtained and then compared. The objective of this work is to use FNLP and IFO techniques for multi-objective inventory model and to compare these techniques through numerical results. The major goal of the paper is to find optimal quantity to be replenished and identify time point when shortages will occur. In this paper FNLP and IFO are applied to multi item multi-objective inventory model with budget and warehouse space constraint and investigating for multi-objective inventory model which method either FNLP or IFO gives efficient solution. In case of maximization objective IFO works well than FNLP while in case of minimization FNLP works better. By observing objectives, the above methods can apply to various inventory problems. All these results along with relation of profit and shortage cost with budget, warehouse space is studied through sensitivity analysis. The result shows that the IFO better results for maximizing profit while FNLP works better in case of minimizing shortage cost. © 2019, Springer Nature India Private Limited.
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