The truck–shovel system is the most common material transportation system in open-pit mines. The configuration of trucks and shovels directly affects the efficiency and cost of transportation in open-pit mines. Under the condition that the types and quantities of trucks and shovels are known, in order to obtain the optimal configuration scheme in the open-pit mine transportation system this paper presents a method to determine the optimal scheme by conducting experiments based on the simulation truck–shovel system model in Flexsim software. We test candidate configuration schemes that are solved by the mathematical model with daily minimum production and expected profit constraints in the simulation model, and finally obtain the optimal truck–shovel configuration scheme that meets the ore output requirements of each loading point. Through simulation experiments, the daily production of the optimal truck–shovel configuration scheme is 3.75% higher than that of the original mine scheme and the profit is increased by 3.85%. The results show that the open-pit truck–shovel system constructed by Flexsim has great research potential and value for the optimization of truck–shovel configuration schemes.
During the operation of open-pit mining, the loading position of a haulage truck often changes, bringing a new challenge concerning how to plan an optimal truck transportation path considering the terrain factors. This paper proposes a path planning method based on a high-precision digital map. It contains two parts: (1) constructing a high-precision digital map of the cutting zone and (2) planning the optimal path based on the modified Hybrid A* algorithm. Firstly, we process the high-precision map based on different terrain feature factors to generate the obstacle cost map and surface roughness cost map of the cutting zone. Then, we fuse the two cost maps to generate the final cost map for path planning. Finally, we incorporate the contact cost between tire and ground to improve the node extension and path smoothing part of the Hybrid A* algorithm and further enhance the algorithm’s capability of avoiding the roughness. We use real elevation data with different terrain resolutions to perform random tests and the results show that, compared with the path without considering the terrain factors, the total transportation cost of the optimal path is reduced by 10%–20%. Moreover, the methods demonstrate robustness.
In order to improve the car-hailing service quality, this paper adopted system dynamics. Based on the simulation of the system model, the improvement strategy of car-hailing service quality was proposed. The system boundary was determined from the car-hailing service environment quality, service interaction quality, service result quality, and other aspects. Relying on Vensim policy simulation function, this paper simulated the impact of car-hailing service quality changes on the car-hailing about the business income of the vehicle, the number of users of the car-hailing, the size of the car-hailing, and the GDP of the city. Research shows that the improvement of the network service quality of the vehicle service to the network business Revenue, network users, number of vehicles, and urban GDP have a positive effect.
Abstract. At present, when flight seasonal routing management departments make the flight plans, there is a lack of quantitative assessment of the actual execution of the delay together with the technology for finding the potential key link of flight delays. In order to enhance the scientificity and rationality of flight seasonal scheduling, this paper proposes a flight schedule optimization model based on historical data, for the purpose of reducing airline's request deviation, i.e., the time difference between allocated time slots and airline requets and operational delays. This model construct an object function which make the total operating and planned delay minimum and firstly introduce corridor capacity as constraint. In the experimental part based on the historical data of Hangzhou Xiaoshan Airport, we use Hungarian algorithm to give solutions of this model and prove the feasibility and effectiveness.
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