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.

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.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2018030
Classification : 03C98
Mots-clés : 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://www.numdam.org/articles/10.1051/ro/2018030/}
}
TY  - JOUR
AU  - Phuc, Phan Nguyen Ky
AU  - Yu, Vincent F.
AU  - Chou, Shuo-Yan
AU  - Tsao, Yu-Chung
TI  - Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model
JO  - RAIRO - Operations Research - Recherche Opérationnelle
PY  - 2018
SP  - 1261
EP  - 1275
VL  - 52
IS  - 4-5
PB  - EDP-Sciences
UR  - http://www.numdam.org/articles/10.1051/ro/2018030/
DO  - 10.1051/ro/2018030
LA  - en
ID  - RO_2018__52_4-5_1261_0
ER  - 
%0 Journal Article
%A Phuc, Phan Nguyen Ky
%A Yu, Vincent F.
%A Chou, Shuo-Yan
%A Tsao, Yu-Chung
%T Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model
%J RAIRO - Operations Research - Recherche Opérationnelle
%D 2018
%P 1261-1275
%V 52
%N 4-5
%I EDP-Sciences
%U http://www.numdam.org/articles/10.1051/ro/2018030/
%R 10.1051/ro/2018030
%G en
%F RO_2018__52_4-5_1261_0
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. http://www.numdam.org/articles/10.1051/ro/2018030/

[1] E. Almehdawe and B. Mantin, Vendor managed inventory with a capacitated manufacturer and multiple retailers: Retailer versus manufacturer leadership. Int. J. Prod. Econ. 128 (2010) 292–302 | DOI

[2] F.M. Bass, A new product growth for model consumer durables. Manag. Sci. 15 (1969) 215–227 | DOI | Zbl

[3] F.M. Bass, T.V. Krishnan and D.C. Jain, Why the Bass model fits without decision variables. Market. Sci. 13 (1994) 203–223 | DOI

[4] S. Cavalieri and P. Gaiardelli, Hybrid genetic algorithms for a multiple-objective scheduling problem. J. Intel. Manuf . 9 (1998) 361–367 | DOI

[5] L.A. Fourt and J.W. Woodlock, Early prediction of market success for new grocery products. J. Market. 25 (1960) 31–38 | DOI

[6] J.J. Grefenstette, Optimization of control parameters for genetic algorithms. IEEE Xplore: Systems, Man, and Cybernetics, Part B 16 (1986) 122–128

[7] D. Horsky and L.S. Simon, Advertising and the diffusion of new products. Market. Sci. 2 (1983) 1–17 | DOI

[8] A.K. Jain and H.A. Elmaraghy, Single process plan scheduling with genetic algorithm. Prod. Plan. Control 8 (1997) 363–376 | DOI

[9] D. Kim and J.A. Fessler, Optimized first-order methods for smooth convex minimization. Math. Prog. 151 (2016) 8–107 | Zbl

[10] K.C. Kiwiel, Convergence and efficiency of subgradient methods for quasiconvex minimization. Math. Prog. (Series A) 90 (2001) 1–25 | DOI | Zbl

[11] T.V. Krishnan and D.C. Jain, Optimal dynamic advertising policy for new products. Manag. Sci. 52 (2006) 1957–1969 | DOI | Zbl

[12] L. Lu, A one-vendor multi-buyer integrated inventory model. Eur. J. Oper. Res. 81 (1995) 312–323 | DOI | Zbl

[13] V. Mahajan, R.A. Peterson, A.K. Jain and N. Malhotra, A new product growth model with a dynamic market potential. Long Range Plan. 12 (1979) 51–58 | DOI

[14] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, New York (1996) | DOI | Zbl

[15] C.V. Nikolopoulos and A.N. Yannacopoulos, A model for optimal stopping in advertisement. Nonlinear Anal. Real World Appl. 11 (2010) 1229–1242 | DOI | Zbl

S.C. Niu, A stochastic formulation of the Bass model of new product diffusion. Math. Probl. Eng. 8 (2002) 249–263 | DOI | Zbl

Cité par Sources :