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Solving Fuzzy Multi-Item Economic Order Quantity Problems via Fuzzy Ranking Functions and Particle Swarm Optimization

In: Metaheuristics in the Service Industry

Author

Listed:
  • Adil Baykasoğlu

    (University of Gaziantep)

  • Tolunay Göçken

    (University of Gaziantep)

Abstract

Determination of the Economic Order Quantities (EOQ) is critical for many service and manufacturing industries in order to achieve optimal operating conditions. Although there are numerous studies on solving EOQ problems with crisp parameters, the number of studies which consider EOQ problems with fuzzy parameters is very limited in the literature. In this paper, a multi-item EOQ problem with fuzzy parameters is considered. All of the parameters of the multi-item EOQ problem are defined as triangular fuzzy numbers. Afterwards the fully fuzzy 11 mathematical programming problem is solved directly (without any transformation process) by making use of fuzzy ranking functions and the particle swarm optimization algorithm. It is observed that the proposed approach is eligible in solving the present problem.

Suggested Citation

  • Adil Baykasoğlu & Tolunay Göçken, 2009. "Solving Fuzzy Multi-Item Economic Order Quantity Problems via Fuzzy Ranking Functions and Particle Swarm Optimization," Lecture Notes in Economics and Mathematical Systems, in: Kenneth Sörensen & Marc Sevaux & Walter Habenicht & Martin Josef Geiger (ed.), Metaheuristics in the Service Industry, chapter 3, pages 33-44, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-00939-6_3
    DOI: 10.1007/978-3-642-00939-6_3
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