transportation scheduling
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2022 ◽  
Author(s):  
Koki Meno ◽  
Ayanori Yorozu ◽  
Akihisa Ohya

Abstract In this study, a method was developed to address the automated guided vehicle (AGV) transportation scheduling problem. For deliveries in factories and warehouses, it is necessary to quickly plan a feasible transportation schedule without delay within a specified time. This study focused on obtaining a transport schedule without delay from the specified time while maintaining the search for a better solution during the execution of the transport task. Accordingly, a method was developed for constructing a solution with a two-dimensional array of delivery tasks for each AGV, arranged in the order in which they are executed, as well as for searching for a schedule by performing exchange and insertion operations. For the exchange and insertion, a method that considers the connectivity between the end point of a task and the start point of the next task was adopted. To verify the effectiveness of the proposed method, numerical simulations were performed assuming an actual transportation task.


2021 ◽  
Vol 16 (3) ◽  
pp. 359-371
Author(s):  
A.Q. Huang ◽  
Y.Q. Zhang ◽  
Z.F. He ◽  
G.W. Hua ◽  
X.L. Shi

Electric vehicle battery recharging on the swapping mode has grown up as an important option other than the plug-in recharging mode in China, given that several auto giants have been dedicated in constructing their battery swapping systems. However, the lack of effective operational methods on battery recharging and transportation scheduling has aroused a big challenge on the practical application of the swapping mode, which enables the necessity of our work. This study proposes a joint optimization model of recharging and scheduling of electric vehicle batteries with a dynamic electricity price system which is able to identify the optimal charging arrangement (the recharging time and the quantity of recharging batteries) as well as the optimal transportation arrangement (the transportation time and the quantity of transporting batteries). For the validation purpose, a numerical study is implemented based on dynamic electricity prices in Beijing. A sensitivity analysis of parameters is carried out to increase the robustness and provide more managerial insights of the model.


2021 ◽  
Vol 16 (7) ◽  
pp. 2554-2570
Author(s):  
Weixin Wang ◽  
Shizhen Wang ◽  
Jiafu Su

Carbon emission constraints and trading policies in e-commerce environments have brought huge challenges to the operation of supply chain enterprises. In order to ensure the good operation of the e-commerce supply chain in a low-carbon environment, a supply chain scheduling optimization method based on integration of production and transportation with carbon emission constraints is proposed; we use it to analyze the impact of centralized decision-making mode and decentralized decision-making mode on supply chain scheduling and establish a scheduling optimization model that aims at optimal carbon emissions and costs. A multilevel genetic algorithm was designed according to the characteristics of the model, and numerical examples are used to verify the effectiveness of the model and algorithm. The results show that the centralized decision-making mode plays the role of the carbon emission constraints to the greatest extent; the carbon emissions and the cost are smallest in the centralized decision-making mode. The decentralized decision-making mode leads to the overall cost preference of the supply chain due to separate decisions made by enterprises, and the carbon emissions in the supply chain are greater. Transportation experts, business managers and government departments are interesting for integrated production and transportation scheduling in e-commerce supply chain with carbon emission constraints. Further research should address integrated production and transportation scheduling in dual-channel low supply chains.


Algorithms ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 108
Author(s):  
Xinfeng Yang ◽  
Yicheng Qi

The optimization of bus scheduling is a key method to improve bus service. So, the purpose of this paper is to address the regional public transportation dispatching problem, while taking into account the association between the departure time of buses and the waiting time of passengers. A bi-objective optimization model for regional public transportation scheduling is established to minimize the total waiting cost of passengers and to maximize the comprehensive service rate of buses. Moreover, a NSGA-II algorithm with adaptive adjusted model for crossover and mutation probability is designed to obtain the Pareto solution set of this problem, and the entropy weight-TOPSIS method is utilized to make a decision. Then the algorithms are compared with examples, and the results show that the model is feasible, and the proposed algorithms are achievable in solving the regional public transportation scheduling problem.


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