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Using AI Approach to Solve a Production-Inventory Model with a Random Product Life Cycle Under Inflation

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Computational Science and Its Applications – ICCSA 2007 (ICCSA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4705))

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Abstract

This paper considers a production-inventory system with inflation and a random life cycle. Two conditions are discussed: the first is when the product life cycle ends in the production stage and the second is when the product life cycle ends in the non-production stage. We develop a genetic algorithm to find the optimal period time and the lowest expected total cost. Numerical examples and sensitivity analyses are given to validate the results of the production model.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Chung Yuan Christian University, Chungli 32023, Taiwan

    H. M. Wee

  2. Logistics Management Department, Takming College, Taipei 114, Taiwan

    Jonas C. P. Yu

  3. Industrial Engineering & Management Department, St. John’s & St. Mary’s Institute of Technology, Tamsui, Taipei 25135, Taiwan

    P. C. Yang

Authors
  1. H. M. Wee
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  2. Jonas C. P. Yu
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  3. P. C. Yang
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Editor information

Osvaldo Gervasi Marina L. Gavrilova

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© 2007 Springer-Verlag Berlin Heidelberg

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Wee, H.M., Yu, J.C.P., Yang, P.C. (2007). Using AI Approach to Solve a Production-Inventory Model with a Random Product Life Cycle Under Inflation. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4705. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74472-6_60

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  • DOI: https://doi.org/10.1007/978-3-540-74472-6_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74468-9

  • Online ISBN: 978-3-540-74472-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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