• Title of article

    Performance evaluation in aggregate production planning using integrated RED-SWARA method under uncertain condition

  • Author/Authors

    Khalili, J Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Qazvin Branch - Islamic Azad University - Qazvin, Iran , Alinezhad, A Department of Industrial Engineering - Faculty of Industrial and Mechanical Engineering - Qazvin Branch - Islamic Azad University - Qazvin, Iran

  • Pages
    15
  • From page
    912
  • To page
    926
  • Abstract
    Nowadays, increasing the eciency of production and determining the proper tools and methods of measuring performance are the biggest challenges faced by managers in the context of signicant competition among companies and manufacturing centers. In aggregate production planning, performance evaluation is necessary for reducing the waste of resources due to the common use of resources for product family manufacturing. The present study aims to evaluate the performance of the Aggregate Production Planning (APP). In this regard, the optimal values were determined by the multi-objective Grey Aggregate Production Planning (GAPP) model, and the weights of the input and output indicators for the performance evaluation were characterized by the Step-wise Weight Assessment Ratio Analysis (SWARA) method. Further, the eciency of Decision-Making Units (DMUs) was determined by the Ratio Eciency Dominance (RED) model. Then, DMUs were ranked. In the case study of the automobile parts manufacturing industry in Iran, sensitivity analysis was performed on the proposed model and its eects were evaluated. The results indicated that the proposed model had a higher degree of accuracy in evaluating performance than previous models, thus helping managers make better decisions so that the eciency and the waste of resources can increase and decrease, respectively
  • Keywords
    Grey system theory , RED model , SWARA method , Performance evaluation , Aggregate production planning
  • Journal title
    Scientia Iranica(Transactions E: Industrial Engineering)
  • Serial Year
    2021
  • Record number

    2679087