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Inventory Models for Deteriorating Items with Variable Selling Price under Stock-Dependent Demand

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6423))

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Abstract

In this paper, we consider the problem of determining the optimal replenishment policy for deteriorating items with variable selling prices under stock-dependent demand, in order to match realistic circumstances. The inventory problem of this study includes without shortages as well as complete backlogging models. A theoretical analysis of the existence and uniqueness of the optimal solutions without shortages and with complete backlogging is presented. Numerical examples of the parameters are also presented to illustrate these two models. Finally, we compare the optimal solutions without shortages to those with complete backlogging.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering & Management, Ching Yun University, Jung-Li, 320, Taiwan

    Yen-Wen Wang, Chih-Te Yang & August Tsai

  2. Graduate Institute of Management Sciences, Tamkang University, Tamsui, Taipei, 251, Taiwan

    Chiou-Ping Hsu

Authors
  1. Yen-Wen Wang
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  2. Chih-Te Yang
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  3. August Tsai
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  4. Chiou-Ping Hsu
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Wang, YW., Yang, CT., Tsai, A., Hsu, CP. (2010). Inventory Models for Deteriorating Items with Variable Selling Price under Stock-Dependent Demand. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_38

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  • DOI: https://doi.org/10.1007/978-3-642-16696-9_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16695-2

  • Online ISBN: 978-3-642-16696-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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