Data-driven multi-target strip mine truck path optimization method
A path optimization and data-driven technology, applied in data processing applications, forecasting, instruments, etc., can solve problems such as the transportation path of metal open-pit mining trucks, and achieve the effects of reducing transportation costs, improving economic benefits, and improving transportation efficiency
Pending Publication Date: 2022-05-06
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology
[0004] In order to overcome the shortcomings of the above-mentioned prior art and solve the problem of the transportation path of the current metal open-pit mine truck fleet, the purpose of the present invention is to provide a data-driven multi-objective open-pit mine truck route optimization method, which establishes the shortest total transportation distance and minimizes time loss. The open-pit truck path optimization model with the goal of minimizing the penalty cost is designed, and a random forest-assisted optimization algorithm driven by data is designed to solve the multi-objective open-pit truck path optimization model
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[0014] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings and examples.
[0015] The present invention proposes a data-driven multi-objective open-pit mine truck path optimization method. On the basis of the existing mine truck path model, a data-driven random forest agent auxiliary model is introduced, which will include uncertain factors such as road conditions and weather. The historical data is used to guide the search of the improved multi-objective ant colony algorithm (adaptive pheromone update mechanism, improved ant cycle model, Pareto fitness evaluation mechanism), such as figure 1 As shown, it mainly includes the following steps:
[0016] Step 1: According to the mine production demand and indicators, combined with the trade-off relationship between transportation cost and transportation efficiency, and aiming at the shortest total transportation distance and the minimum time loss penalty cost, a mult...
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The invention relates to a data-driven multi-target strip mine truck path optimization method, which comprises the following steps of: constructing a multi-target strip mine truck path optimization model aiming at the shortest total transportation distance and the minimum time loss punishment cost according to actual production requirements and indexes of a mine; on the basis of mine truck historical trajectory data, a data-driven random forest aided optimization algorithm is adopted to solve a multi-target strip mine truck path optimization model, and the algorithm is improved under an optimization framework of an ant colony algorithm, so that a transportation scheme more conforming to the mine production current situation can be efficiently searched. Starting from the actual production condition of the mine, the method has important significance in improving the transportation efficiency, reducing the transportation cost and improving the economic benefits of mine enterprises.
Description
technical field [0001] The invention belongs to the technical field of mining system engineering and mine optimization, and in particular relates to a data-driven multi-objective open-pit mine card path optimization method. Background technique [0002] In recent years, with the deepening application of emerging technologies such as artificial intelligence, big data, Internet of Things, and cloud computing to the mining industry, the global mining industry is undergoing a new technological revolution. Open-pit mining is an important way of mining mineral resources in my country, and its transportation costs account for about 50% of the total production and operation costs. At the same time, mine truck transportation is the main mode of production and transportation of open-pit mines in my country. Therefore, it is a problem that every mining enterprise pays close attention to and urgently needs to be solved to make overall planning for its transportation route, rationally a...
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IPC IPC(8): G06Q10/04G06Q50/02G06Q50/30G06N3/00
CPCG06Q10/047G06Q50/02G06N3/006G06Q50/40Y02T10/40
Inventor 顾清华王倩江松阮顺领冯治东李学现陈露常朝朝
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY