Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System

Houming Fan, Xiaoxue Ren, Zhenfeng Guo and Yang Li
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Houming Fan: Transportation Engineering, Dalian Maritime University, Dalian 116026, China
Xiaoxue Ren: Transportation Engineering, Dalian Maritime University, Dalian 116026, China
Zhenfeng Guo: Transportation Engineering, Dalian Maritime University, Dalian 116026, China
Yang Li: School of Mining Engineering, Liaoning Shihua University, Fushun 113005, China

Sustainability, 2019, vol. 11, issue 22, 1-23

Abstract: Aiming at the truck scheduling problem between the outer yard and multi-terminals, the appointment optimization model of truck is established. In this model, the queue time and the operation time of truck during the appointment period of different terminals are different. Under the restriction of given appointment quotas of each appointment period, determine the arrival amount of trucks in each appointment period. The goal is to reduce carbon emissions and total costs, improve the efficiency of truck scheduling. To solve this model, hybrid genetic algorithm with variable neighborhood search was designed. Firstly, generate chromosomes, and the front part of the chromosome represents the demand for 40 ft containers and the back part represents the demand for 20 ft containers. Then, the route is generated according to the time constraint and appointment quotas of each appointment period. Finally, the neighborhood search strategy is adopted to improve the solution quality. The validity of the model and algorithm were verified by an example. A low-carbon scheduling scheme was obtained under truck appointment system. The results show that the scheduling scheme under truck appointment system uses fewer trucks, improves the efficiency of delivery, reduces the total costs, and it takes into account the requirements of low carbon.

Keywords: carbon emissions; truck appointment system; container terminal; multi-types containers; hybrid genetic algorithm with variable neighborhood search (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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