optimization on production-inventory problem with multistage and varying demand

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ID: 169525
2012
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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.
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gang2012journaloptimization Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Duan Gang;Chen Li;Li Yin-Zhen;Song Jie-Yan;Akhtar Tanweer
Journal Chemico-biological interactions
Year 2012
DOI
10.1155/2012/648262
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