# Improved Genetic Algorithm for Solving Green Path Models of Concrete Trucks
## 2 Fuel Consumption Models  
According to the vehicle engine energy consumption model proposed in [27], factors related to the vehicle path will affect the vehicle fuel consumption, such as the vehicle distance traveled, the total weight of the vehicle, and the angle between the vehicle and the road ramp, so the fuel consumption of the concrete truck varies under different distribution schemes. Figure 1 illustrates the co-operative distribution of concrete to four sites by three \begin{table}
\begin{tabular}{c c c c} \hline \hline
**References** & **Contributions** & **Algorithms** & **Disadvantages** \\ \hline
[8] & The algorithm is improved to solve the GVRP problem. & MA & The universality of the algorithm is difficult to guarantee. \\  & The GVRP model was established with the aim of minimizing total fuel consumption & ACO & The effect of road slope on fuel \\
[10] & by considering some factors that affect vehicle fuel consumption. & & consumption was not considered. \\  & A multi-objective MDVRP model was & GA & Other factors affecting vehicle fuel \\
[11] & established with the aim of minimizing vehicle carbon emission. & GA & consumption are not considered. \\  & A multi-objective MDVRP model was & A multi-objective MDVRP model was & ACO & The load of the vehicle was not taken into account. \\
[12] & established considering the carbon emission cost and driving time. & / & The improved algorithms for solving GVRP are not compared and analyzed. \\
[14] & The GVRP models are classified according to their objective functions. & GA & The fuel consumption of the vehicle is not taken into account. \\  & The factors affecting RMC delivery are & GA & The capacity of the different tankers was not taken into account. \\
[19] & analyzed, and a model is established with minimum delivery time as the target. & GA & The road congestion problem that may be encountered in the actual distribution of tank cars is ignored. \\
[20] & The RMC-scheduling model is established & SA & A method of estimation is used to predict vehicle fuel consumption. \\
[21] & The RMC distribution model is established & / & The time window of distribution and the problem of vehicle failure in the process of distribution are ignored. \\
[22] & A model is proposed for concrete & & It is not conducive to the solution of the model. \\
[23] & companies to adjust their plans to reduce production costs. & / & The method of multi-mixing collaborative distribution is not considered. \\
[24] & RMC delivery is divided into two parts to reduce the difficulty of solving it. & / & The time method of multi-mixing collaborative distribution is not considered. \\
[25] & The RMC distribution model is established & & The article acquiesces that the volume of all tank cars is the same without considering different models. \\
[26] & from the perspective of multi-mixing plant & BA & \\  & co-operative distribution. & & different models. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of research methods and objectives for VRP. concrete-mixing plants. The goal of this study is to establish a green distribution path model for dispatching vehicles when multiple concrete-mixing plants deliver concrete to numerous construction sites, by optimizing the vehicle distribution scheme, to reduce the total fuel consumption of the vehicles. Since vehicle carbon emissions and fuel consumption are positively correlated, the lower the total oil consumption of vehicles during the entire distribution process, the lower the total carbon emissions [28]; hence, the problem solved in this paper belongs to the green VRP. In order to better study the problem, the following assumptions must be established:  
1. Each concrete distribution truck is allowed to depart from the mixing plant to the customer's site only once and is not allowed to return;
2. The mixing plants are able to produce different grades of concrete in time to meet the needs of each site;
3. The maximum transport time required by the site for each mixing plant is the true transport time of the truck;
4.