An Optimal Ordering Decision-making Model with Random Demand Under Carbon Constraint
- *Corresponding Author:
- Weiwei Li
School of Economics and Management
Nanjing University of Information Science and
Technology, 210044, Nanjing, China
Tel: +86 13913807418
E-mail: [email protected]
Received Date September 07, 2015; Accepted DateOctober 07, 2015; Published Date October 17, 2015
Citation: Li W, Zheng W, Dai Y (2015) An Optimal Ordering Decision-making Model with Random Demand Under Carbon Constraint. Arabian J Bus Manag Review 6:176.
Copyright: © 2015 Li W, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Under the increasing pressure to reduce carbon emission, the enterprises need to actively take account into carbon emission, and take low carbon action among daily business activities. This not only relate to the realization of carbon emission goal, but probably efficient solution to our country carbon emission targets. Applying to optimal theory under carbon-constrained, this paper comprehensively include economical cost and environment cost to construct random optimal decision-making model. Then using mat lab numerical analysis, this paper reveals the decision-making mechanism of enterprise ordering making under carbon cap constrained, and provides management implications and future research direction. The result indicates that: An enterprise can significantly reduce carbon emission without significantly increasing cost through adjusting ordering quantity. Enterprise’s carbon emissions show a certain correlation with order quantity when carbon emission cap is within the scope of threshold value, but optimal ordering decision-making has no correlation with carbon emission cap when cap is beyond the scope of threshold value. Caron emission cap is set voluntarily by an enterprise’s decision maker or put forward mandatorily by an external regulatory agency, and its setting should be reasonable and scientific.