This paper addresses a special truck routing optimization problem in open-pit mines based on the minimization of time-varying transport energy consumption. A mixed-integer programming model is formulated to clearly describe the engineering problem, and a series of constraints are deduced to strengthen the model. To ensure that the model has time-varying characteristics, a method to estimate time-varying parameters is proposed by using pattern recognition and trend surface estimation. This time-varying resistance coefficient is mainly used to describe the process of road damage caused by frequent rolling of heavy trucks on the road surface. At the same time, in order to make the truck routing converge to the optimal energy consumption solution quickly, some definitions and properties are then provided based on stochastic theory, and a strategy to improve the computational efficiency of the model is proposed using these properties. Finally, an improved genetic algorithm is designed to solve the model. The results of experiments show that the proposed algorithm is effective and efficient.

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rolling method heavy optimal energy consumption solution engineering pattern recognition minimization of timevarying transport energy genetic algorithm trend surface mixedinteger programming model computational efficiency timevarying resistance coefficient truck routing optimization problem stochastic theory road damage

Guangwei Liu,Senlin Chai,.Optimizing Open-Pit Truck Route Based on Minimization of Time-Varying Transport Energy Consumption. 2019 (),.

Guangwei Liu,Senlin Chai,"Optimizing Open-Pit Truck Route Based on Minimization of Time-Varying Transport Energy Consumption" 2019

Guangwei Liu,Senlin Chai,"Optimizing Open-Pit Truck Route Based on Minimization of Time-Varying Transport Energy Consumption"