Study on the Optimal Path Optimization of Coal Transportation based on Cost Minimization
- DOI
- 10.2991/icedem-17.2017.66How to use a DOI?
- Keywords
- Electric coal; transportation route; Cost minimization; Genetic algorithm
- Abstract
China is a country with abundant coal resources, most provinces and regions are more or less the existence of coal resources, coal size also can be formed, however, are mainly distributed in China's western region of shanxi, shanxi and Inner Mongolia and other regions. And in terms of consumption, they are mainly concentrated in the economy relatively developed provinces, such as the Beijing and Tianjin tang, LiaoZhong south, shanghai-Nanjing Hangzhou and the pearl river delta industrial base, the area of coal consumption as long as from the demand for electricity. For the current situation of the different parts of the coal production and marketing and cross-regional transportation of coal laid the inevitability, makes our country have formed a unique " north coal south" and "west to east" coal transport characteristics. Therefore, electric coal production and power generation in China face a serious transportation problem in adverse distribution area. This problem will also become one of the factors that influence China's realization of the Chinese dream. In this paper, a genetic algorithm based on cost minimization control is proposed to solve this problem.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Mingfang Li AU - Shumin Lin PY - 2017/12 DA - 2017/12 TI - Study on the Optimal Path Optimization of Coal Transportation based on Cost Minimization BT - Proceedings of the 2017 International Conference on Economic Development and Education Management (ICEDEM 2017) PB - Atlantis Press SP - 256 EP - 259 SN - 2352-5398 UR - https://doi.org/10.2991/icedem-17.2017.66 DO - 10.2991/icedem-17.2017.66 ID - Li2017/12 ER -