Optimising truckload operations in third-party logistics: A carbon footprint perspective in volatile supply chain

被引:33
作者
Wong, Eugene Y. C. [1 ]
Tai, Allen H. [2 ]
Zhou, Emma [1 ]
机构
[1] Hang Seng Management Coll, Sch Decis Sci, Dept Supply Chain & Informat Management, Hong Kong, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, Dept Appl Math, Hong Kong, Hong Kong, Peoples R China
关键词
Carbon emission; Third-party logistics; Sustainability; Truckload utilisation; ENVIRONMENTAL SUSTAINABILITY; LOAD CONSOLIDATION; TRANSPORTATION; PERFORMANCE; EFFICIENCY; POLICIES; DESIGN;
D O I
10.1016/j.trd.2018.06.009
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With government and customers driving third-party logistics seeking opportunities to improve operation efficiencies and mitigating carbon emissions in the supply chain, third-party logistics firms have been striving to improve their truckload utilization and vehicle routing operations, especially in emission-regulated countries and volatile business environment. Traditional literature has focused on either truckload utilization or vehicle routing operations but seldom integrating carbon emission mitigation in their daily trucking operations. This paper delineates the operation review of three third-party logistics firms in Hong Kong and develops an organisation based carbon emission measurement metrics for logistics operations. The truckload utilization and routing performance are reviewed, followed by a correlation analysis on the truckload utilization against truck capacity, loading volume, fuel consumption, truck size, travelling distances and number of destinations. An integrated carbon-driven multi-criteria model is developed achieving carbon emission reduction initiatives, time and distance cost penalty, minimizing number of trucks, and improving truck utilization. The integrated mathematical model has been developed into a simulation system which has been tested with evaluated results. The mathematical model is enhanced for the set of cargo items and vehicle fleet with additional factors of arrival time slots and weight. The model assists traffic planners to reduce cargo planning time and optimize the truckload operations. Further development will be focused on adding the dimensions of pallet loading operations and exception rules for customer loading requirements.
引用
收藏
页码:649 / 661
页数:13
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