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Control Number314027
Date and Time of Latest Transaction20150706094035.AM
General Information150706s |||||||||b ||00|||
Cataloging SourceSTII-DOST
Local Call NumberScienceDirect
Main Entry - Personal NameMalekly, H.
 Al-e-hashem, S.M.J. Mirzapour
 Aryanezhad, M.B.
Title StatementA multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty by S.M.J. Mirzapour Al-e-hashem, H. Malekly and M.B. Aryanezhad
Physical Descriptionpages 28-42 computer file; text; 783kb
Summary, Etc.Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.04
Subject Added Entry - Topical TermSocial sciences04
 Labor productivity -- Analysis04
 Business logistics -- Analysis04
 Aggregate production planning
LocationDOST STII ScienceDirect NONPRINTS NP 14-16490 1 14-16490 Online/Download 2012-01-19
  
     
 
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Department of Science and Technology
Science and Technology Information InstituteScienceDirect
  
     
 
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