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Optimization on Production‐Inventory Problem with Multistage and Varying Demand

Author

Listed:
  • Duan Gang
  • Chen Li
  • Li Yin-Zhen
  • Song Jie-Yan
  • Akhtar Tanweer

Abstract

This paper addresses production‐inventory problem for the manufacturer by explicitly taking into account multistage and varying demand. A nonlinear hybrid integer constrained optimization is modeled to minimize the total cost including setup cost and holding cost in the planning horizon. A genetic algorithm is developed for the problem. A series of computational experiments with different sizes is used to demonstrate the efficiency and universality of the genetic algorithm in terms of the running time and solution quality. At last the combination of crossover probability and mutation probability is tested for all problems and a law is found for large size.

Suggested Citation

  • Duan Gang & Chen Li & Li Yin-Zhen & Song Jie-Yan & Akhtar Tanweer, 2012. "Optimization on Production‐Inventory Problem with Multistage and Varying Demand," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
    • Handle: RePEc:wly:jnljam:v:2012:y:2012:i:1:n:648262
    DOI: 10.1155/2012/648262
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    References listed on IDEAS

    as
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