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Multi-item Fuzzy Inventory Model with Three Constraints: Genetic Algorithm Approach

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

In this paper a multi-item fuzzy inventory model under total production cost, total storage space and number of orders constraints is solved with a Genetic Algorithm. In this model, the production cost and set up cost are directly proportional to the respective quantities, unit production cost is inversely related to the demand and set up cost is assumed to vary directly with lot size. Also Shortages are allowed. However this approach has been applied to solve the model under fuzzy objective of cost minimization and imprecise constraints on storage space, number of orders and production cost with imprecise inventory costs. This model has been formulated as FNLP problem and then converted to equivalent crisp decision making problems and solved by a Genetic Algorithm. Finally the model is illustrated with a numerical example.

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Author information

Authors and Affiliations

  1. Department of Industrial Management, Vali-e-Asr University of Rafsanjan, Rafsanjan, Kerman, Iran

    Jafar Rezaei

  2. Department of Computer Sciences, Vali-e-Asr University of Rafsanjan, Rafsanjan, Kerman, Iran

    Mansoor Davoodi

Authors
  1. Jafar Rezaei
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  2. Mansoor Davoodi
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Rezaei, J., Davoodi, M. (2005). Multi-item Fuzzy Inventory Model with Three Constraints: Genetic Algorithm Approach. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_152

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  • DOI: https://doi.org/10.1007/11589990_152

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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