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**Optimization on production-inventory problem with multistage and varying demand.**
*(English)*
Zbl 1264.90003

Summary: We address a 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.

### MSC:

90B05 | Inventory, storage, reservoirs |

90C30 | Nonlinear programming |

90B06 | Transportation, logistics and supply chain management |

65K10 | Numerical optimization and variational techniques |

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\textit{G. Duan} et al., J. Appl. Math. 2012, Article ID 648262, 17 p. (2012; Zbl 1264.90003)

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### References:

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