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A Batching Problem With Learning Effect Considerations

Author

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  • WEN-HUA YANG

    (Department of Business Administration, Chaoyang University of Technology, 168, Gifong E. Rd., Wufong, Taichung County, 413, Taiwan)

Abstract

Consider a batch-sizing problem, where all jobs are identical or similar, and aunitprocessing time(p = 1)is specified for each job. To minimize the total completion time of jobs, partitioning jobs into batches may be necessary. Learning effect from setup repetition makes small-sized batches; on the contrary, job's learning effect results in large-sized batches. With their collaborative influence, we develop a forward dynamic programming (DP) algorithm to determine the optimal number of batches and their optimal integer sizes. The computation effort required by this DP algorithm is a polynomial function of job size.

Suggested Citation

  • Wen-Hua Yang, 2009. "A Batching Problem With Learning Effect Considerations," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(02), pages 307-317.
    • Handle: RePEc:wsi:apjorx:v:26:y:2009:i:02:n:s0217595909002213
    DOI: 10.1142/S0217595909002213
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