Supply chain network equilibrium (SCNE) model can provide many important results for supply chain network. Such as the production of product, the trade volume between supply chain members, and product price, etc. In this paper, the authors analyze the supply chain equilibrium and transportation network efficiency based on MSA algorithms and multilayer decision model. The super network equilibrium problem was converted to transportation network equilibrium problem, and then was planned and resolved. An example was introduced in the paper, and the model was solved. The results showed that the expansion of congestion link capacity would improve the efficiency of supply chain network. New link can cause a significant change in the distribution channel of supply chain network. Those all prove that model can be used to study the interact between related policy of road transport and benefit of supply chain network. At the same time, the model built in this paper can be applied when extended in some direction, which is the next step of research work.
M.S.Bazaraa, H.D.Sherali and C.M.Shetty, Nonlinear Programming: Theory and Algorithms.John Wiley & Sons, New York, 1993.
2.
F.Bernstein and A.Federgruen, Pricing and replenishment strategies in a distribution system with competing retailers, Naval Research Logistics51 (2003), 409–426.
3.
G.P.Cachon, P.H.Zipkin, Competitive and cooperative inventory policies in a two-stage supply chain, Management Science45 (1999), 936–953.
4.
A.Nagurney, In: On the relationship between supply chain and transportation network equilibria: a supernetwork equivalence with computations, Transportation Research E42 (2006), 293–316.
5.
H.Chen and H.Chou, In: A time-dependent supply chain equilibrium problem. In: Lau, Y.C., Unhelkar, B. (Eds.), Global Integrated Supply Chain Systems:Analysis and Design.Idea Group Inc., USA (2004).
6.
A.Nagurney, In: On the relationship between supply chain and transportation network equilibria: a supernetwork equivalence with computations, Transportation Research E42 (2006), 293–316.
Y.Li and Y.H.Jin, Racing to market leadership: Product launch and upgrade decisions, International Journal of Production Economics119(2) (2009), 284–297.
9.
C.Milliou, E.Petrakis, Timing of technology adoption and product market competition, International Journal of Industrial Organization29(5) (2011), 513–523.
10.
A.Rahman and R.Loulou, Technology acquisition with technological progress: effects of expectations, rivalry and uncertainty, European Journal of Operational Research129(1) (2001), 159–185.
11.
M.Porter, Competitive Strategy, New York: Free Press, 1980.
12.
U.Doraszelski, Innovations, improvements, and the optimal adoption of new technologies, Journal of Economic Dynamics & Control28(7) (2004), 1461–1480.
13.
K.J.M.Huisman and P.M.Kort, Strategic investment in technological innovations, European Journal of Operational Research144(1) (2003), 209–223.
14.
D.Gilo, Y.Moshe and Y.Spiegel, Cross ownership and tacit collusion, RAND J Econ.37(1) (2006), 81–99.
15.
R.Jain and R.Pal, Mixed Duopoly, Cross-ownership and partial privatization, Journal of Economics107(1) (2012), 45–70.
16.
I.Macho-Stadler and T.Verdier, Strategic managerial incentives and cross ownership structure: A note, J Econ.53(3) (1991), 285–297.
17.
A.Nishimori and H.Ogawa, Do firms always choose excess capacity, Economics Bulletin12(2) (2004), 1–7.
18.
Y.X.Chen and Y.Song, Emergency response capability assessment of emergency supply chain coordination mechanism based on hesitant fuzzy information [J], International Journal of Simulation Modelling13(4) (2014), 485–496.
19.
B.C.Giri and S.Bardhan, Coordinating a supply chain under uncertain demand and random yield in presence of supply disruption [J], International Journal of Production Research53(16) (2015), 5070–5084.
20.
B.C.Giri and S.Bardhan, Coordinating a supply chain with backup supplier through buyback contract under supply disruption and uncertain demand [J], International Journal of Systems Science Operations & Logistics1(4) (2014), 193–204.
21.
X.U.Hong, G.H.Shi and S.O.Management, Supply chain coordination mechanism with asymmetric information and cost disruption under nonlinear demand function [J], Science-Technology and Management, 2015.
22.
However.Emergency Coordination Model of Fresh Agricultural Products' Three-Level Supply Chain with Asymmetric Information [J].Mathematical Problems in Engineering2016, (2016-3-22), 2016(3), (2016), 1–9.
23.
Y.L.Huang, C.Yang, S.J.Jiang, et al.Influenza Vaccine Supply Chain Coordination with Reordering Opportunities under Partial Information [J], Operations Research & Management Science, 2015.
24.
A.Toptal and B.Çetinkaya, How supply chain coordination affects the environment: a carbon footprint perspective, Annals of Operations Research (2015), 1–33.
25.
Mohamad Y.Jaber, Christoph H.Glock and Ahmed M.A.El Saadany, Supply chain coordination with emissions reduction incentives, International Journal of Production Research51(1) (2013), 69–82.
26.
W.Shang and L.Yang, Contract negotiation and risk preferences in dual-channel supply chain coordination, International Journal of Production Research53(16) (2015), 1–20.
27.
S.Swami and J.Shah, Channel coordination in green supply chain management, Journal of the Operational Research Society64(3) (2013), 336–351.
28.
A.Mateen, A vendor-managed inventory scheme as a supply chain coordination mechanism, International Journal of Production Research53(1) (2015), 13–24.
29.
A.Kamali, S.M.T.F.Ghomi and F.Jolai, A multi-objective quantity discount and joint optimization model for coordination of a single-buyer multi-vendor supply chain, Computers & Mathematics with Applications62(8) (2011), 3251–3269.
30.
S.Saha, S.P.Sarmah and I.Moon, Dual channel closed-loop supply chain coordination with a reward-driven remanufacturing policy, International Journal of Production Research54(5) (2016), 1–15.
