Research Article
Multi Attribute Decision Making Approach to Optimize the Product Mix in Assignment Problems using Fuzzy Group Parameters
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 26 - Issue 11 |
| Published: July 2011 |
| Authors: B. Chellappa, S.V. Manemaran |
10.5120/3165-3999
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B. Chellappa, S.V. Manemaran . Multi Attribute Decision Making Approach to Optimize the Product Mix in Assignment Problems using Fuzzy Group Parameters. International Journal of Computer Applications. 26, 11 (July 2011), 1-6. DOI=10.5120/3165-3999
@article{ 10.5120/3165-3999,
author = { B. Chellappa,S.V. Manemaran },
title = { Multi Attribute Decision Making Approach to Optimize the Product Mix in Assignment Problems using Fuzzy Group Parameters },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 26 },
number = { 11 },
pages = { 1-6 },
doi = { 10.5120/3165-3999 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A B. Chellappa
%A S.V. Manemaran
%T Multi Attribute Decision Making Approach to Optimize the Product Mix in Assignment Problems using Fuzzy Group Parameters%T
%J International Journal of Computer Applications
%V 26
%N 11
%P 1-6
%R 10.5120/3165-3999
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Inventory models in which the demand rates on the inventory level are based on the common real life observation that greater product availability tends to stimulate more sales. Theory of constraints (TOC) is a production planning philosophy that tries to improve the throughput of the system management of inventory levels. Due to the existing of inventory levels in a production system the demands of all products can not be fully met. So one of the most important decisions made in production systems is product mix problem. Although many algorithms have been developed in the fields using the concept of theory of constraints. This paper benefits from a variety of advantages. In order to consider the importance of all inventory levels, group decision making approach is applied and the optimal product mix is reached. In the algorithm presented in this paper, each inventory level is considered as a decision maker. The new algorithm benefits from the concept of fuzzy group decision making and optimizes the product mix problem in inventory environment where all parameters are fuzzy values.
References
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