Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms.

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order pi...

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Publicado en:Scientific World Journal pp. 246578 - 246579
Autores principales: Azadnia, Amir Hossein, Taheri, Shahrooz, Ghadimi, Pezhman, Mat Saman, Muhamad Zameri, Wong, Kuan Yew, Saman, Muhamad Zameri Mat
Formato: Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms.
      aug:
        au:
          Azadnia, Amir Hossein
          Taheri, Shahrooz
          Ghadimi, Pezhman
          Mat Saman, Muhamad Zameri
          Wong, Kuan Yew
          Saman, Muhamad Zameri Mat
        affil: Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, Johor Bahru, 81310 UTM Skudai, Malaysia.
      sug:
        subj:
          Algorithms
          Data Mining Methods
          Resource Databases
          Decision Support Techniques
          Equipment and Supplies
          Mathematics
          Information Systems
      ab: One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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