Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1261-1275

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The Bass model offers several successful applications in forecasting the diffusion process of new products. Due to its potential and flexibilities, the application of this model is not only limited now to forecasting, but also extends to other fields such as analyzing a supply chain’s responses, optimizing production plans, and so forth. This study investigates inventory and production policies in a two-stage supply chain with one manufacturer and one retailer, in which the market demand process follows the Bass diffusion model. The model assumes the market parameters and essential information are available and ready for access. This study then applies dynamic programming and heuristic algorithm to find the optimal policies for each stage under different scenarios.

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Accepté le :
DOI : 10.1051/ro/2018030
Classification : 03C98
Keywords: Bass model, dominant, subordinate, inventory management, production plan

Phuc, Phan Nguyen Ky 1 ; Yu, Vincent F. 1 ; Chou, Shuo-Yan 1 ; Tsao, Yu-Chung 1

1
@article{RO_2018__52_4-5_1261_0,
     author = {Phuc, Phan Nguyen Ky and Yu, Vincent F. and Chou, Shuo-Yan and Tsao, Yu-Chung},
     title = {Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the {Bass} diffusion model},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {1261--1275},
     publisher = {EDP-Sciences},
     volume = {52},
     number = {4-5},
     year = {2018},
     doi = {10.1051/ro/2018030},
     zbl = {1418.90021},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1051/ro/2018030/}
}
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Phuc, Phan Nguyen Ky; Yu, Vincent F.; Chou, Shuo-Yan; Tsao, Yu-Chung. Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1261-1275. doi: 10.1051/ro/2018030

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