Developing a Multi-Product Economic Production Quantity Model To Fuzzy Sense Using of Signed Distance Method

Today, inventory management issue has become a concern for a lot of organizations and it is the most necessary issues for organizations by production and inventory plan implementing. Among inventory models, models based on economic production quantity are of the most practical models. Each of the ec...

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书目详细资料
Main Authors: Mohammad Khodashenas, Hamidreza Salmani Mojaveri, Fatemeh Mohammadnezhad Chari
格式: 文件
语言:English
出版: Petra Christian University 2013-01-01
丛编:Jurnal Teknik Industri
主题:
在线阅读:http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/18706
实物特征
总结:Today, inventory management issue has become a concern for a lot of organizations and it is the most necessary issues for organizations by production and inventory plan implementing. Among inventory models, models based on economic production quantity are of the most practical models. Each of the economic production quantity is based on set of para­me­ters that are estimated by experts and decision makers. Since uncertainty exists in real world, it is difficult for experts to estimate parameters, accurately. Therefore, in such situation, using economic production quantity under non-integer conditions would be more appropriate than the crisp conditions and also under such conditions organizations have to determine their cumu­la­tive production in their supply chain in fuzzy sense. In this paper, a multi-product economic production quantity (EPQ) model, under fuzzy conditions, has been fuzzified and optimized by using signed distance method in order to minimize all costs. a numerical example and sensitivity analysis have also provided to illustrate the practical use of the proposed method.
ISSN:1411-2485