Multi-objective model for logistics distribution programming considering carbon emission and service level
- https://doi.org/10.2991/iccte-17.2017.67How to use a DOI?
- Logistics distribution network; carbon emissions; logistics service level; multi-objective; priority-based tabu search algorithm
In order to seek the low-carbon environmental protection and high service level of logistics distribution,a multi-objective optimization model of logistics distribution network is proposed.Firstly,the multi-objective optimization model of logistics distribution network is established by using the multi-objective optimization theory,which takes the total network logistics cost as the minimum,the least carbon emissions and the maximization logistics service level as the goal.Secondly,the fuzzy programming method is used to transform the multi-objective programming model into a single objective programming model,and the tabu search algorithm based on priority is used to solve the model.And the model and the algorithm are verified by example.The results shows that the 10 solutions and 10 logistic distribution schemes are affected by the subjective preferences of the decision-makers by solving the mutli-objective optimization model.In addition,the total cost of the logistics of each scheme is inversely proportional to the level of service.A scientific and feasible logistics network planning method with low carbon and high customer satisfaction is obtained.
- © 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 - Tong He PY - 2017/07 DA - 2017/07 TI - Multi-objective model for logistics distribution programming considering carbon emission and service level BT - Proceedings of the 2017 2nd International Conference on Civil, Transportation and Environmental Engineering (ICCTE 2017) PB - Atlantis Press SP - 378 EP - 388 SN - 2352-5401 UR - https://doi.org/10.2991/iccte-17.2017.67 DO - https://doi.org/10.2991/iccte-17.2017.67 ID - He2017/07 ER -