MATHEMATICAL MODEL FOR INVENTORY CONTROL PROBLEM USING IMPRECISE PARAMETERS

2018 ◽  
Vol 6 (2) ◽  
pp. 07-12
Author(s):  
Neha Kumari ◽  
Manoj Kumar Mandal ◽  
Arun Prasad Burnwal
Keyword(s):  
Control Problem ◽  
Inventory Control ◽  
Geometric Programming ◽  
Programming Model ◽  
Holding Costs ◽  
Fuzzy Membership Functions ◽  
Inventory Control Problem ◽  
Set Up ◽  
Inventory Holding ◽  
Imprecise Parameters

In this paper, an inventory control problem is discussed using imprecise parameters. The fusion of geometric programming and fuzzy logic is used as imprecise parameters to solve inventory control problems. In inventory, holding costs, set-up costs, etc. may be flexible due to vague information. Fuzzy set theory is used to convert the inventory model crisp to fuzzy for producing flexible output. Compensatory operator is used to aggregate the fuzzy membership functions corresponding to fuzzy sets for fuzzy objectives and constraints. This aggregation gives the overall achievement function and the model known as fuzzy geometric programming model.  

INTERACTIVE FUZZY PROGRAMMING MODEL IN MULTI-OBJECTIVE INVENTORY CONTROL PROBLEM USING VARIOUS OPERATORS

2017 ◽  
Vol 5 (4) ◽  
pp. 18-26
Author(s):  
Neha Kumari ◽  
Arun Prasad Burnwal
Keyword(s):  
Control Problem ◽  
Inventory Control ◽  
Decision Maker ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Programming Approach ◽  
Multi Objective ◽  
Aspiration Levels ◽  
Interactive Fuzzy Programming ◽  
Inventory Control Problem

This paper deals with the interactive fuzzy programming approach for Multi Objective Inventory Control Problem (MOICP). In multi-objective optimization problem, objectives are often non-commensurable and cannot be combined into a single objective. Moreover, the objectives usually conflict with each other in that any improvement of one objective can be achieved only at the expense of another. In real world, all objectives of MOICP are not rigid. Some are rigid and some are fuzzy or all are imprecise. Fuzzy goals are defined by different membership functions through interaction with decision maker. By making the aspiration levels more flexible and by assigning different values to the normal weights to corresponding objectives functions, different solutions are determined to interact with the decision maker.

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