Duan, Gang; Chen, Li; Li, Yin-Zhen; Song, Jie-Yan; Akhtar, Tanweer Optimization on production-inventory problem with multistage and varying demand. (English) Zbl 1264.90003 J. Appl. Math. 2012, Article ID 648262, 17 p. (2012). 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 PDF BibTeX XML Cite \textit{G. Duan} et al., J. Appl. Math. 2012, Article ID 648262, 17 p. (2012; Zbl 1264.90003) Full Text: DOI References: [1] S. K. Goyal and B. C. Giri, “The production-inventory problem of a product with time varying demand, production and deterioration rates,” European Journal of Operational Research, vol. 147, no. 3, pp. 549-557, 2003. · Zbl 1026.90001 [2] C. K. Huang, “An optimal policy for a single-vendor single-buyer integrated production-inventory problem with process unreliability consideration,” International Journal of Production Economics, vol. 91, no. 1, pp. 91-98, 2004. [3] R. M. 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